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pdf | 56.43 MB | English| Isbn:9781394272563 | Author: Shubham Mahajan (Editor), Pethuru Raj (Editor), Amit Kant Pandit (Editor) | Year: 2024 Description: https://ddownload.com/sw16fvlps362 https://rapidgator.net/file/03df9c74daca703f9edbc7f8ffb62552/ https://turbobit.net/4bdrdeakq95o.html

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Free Download Udemy - Learning Basics Of Radiopharmaceuticals Published 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz Language: English | Size: 1.10 GB | Duration: 1h 57m Basics of Radiopharmaceuticals What you'll learn Describe the basic principles of radiopharmaceuticals Discuss the various categories of radiopharmaceuticals Differentiate between SPECT and PET scanners Differentiate between SPECT and PET radiopharmaceuticals Requirements Complete the Radiopharmaceutical Chemistry course (Module 1) Description This course is both an introductory and refresher course to basics of radiopharmaceutical whereby students will be taught the basic principles of radiopharmaceuticals, the various categories of radiopharmaceutical kits and learn to differentiate between SPECT and PET scan and radiopharmaceuticals. In general, this course focuses on simple and practical steps to improve performance, core competencies and essential training for undergraduate or postgraduate students and continuous professional development for personnel working or planning to work in the nuclear medicine department or similar establishment. To ensure greater learning experience, students are encouraged to take the Radiopharmaceutical Chemistry course (Module 1) first before embarking on this course (Module 2). It is crucial to learn some concepts in radiolabeling before understanding the categories of radiopharmaceuticals and why they are prepared as such.This course is tailor-made for learners as listed below:Relevant undergraduate or postgraduate studentsRadiopharmacists or nuclear pharmacistsNuclear medicine technologists and radiographersMedical physicists and medical physics techniciansQuality control/quality assurance personnelMedical doctors and other health care professionalsPharmaceutical and radiation regulatory agency personnelResearchers in the field of radiopharmaceutical researchThe course structure consists of 3 sections. Each section provides the lessons in a step-wise manner for easy comprehension and learning. Videos with innovative animation will help facilitate understanding and quizzes at the end of each section will foster and motivate learning. Upon completion of this course, students will be able to describe the basic principles, categories and detection of radiopharmaceuticals.Learners will earn a completion certificate once all the required responses are appropriately given and quizzes completed. There are a total of 12 videos with an approximate learning time of 2.5 hrs including quizzes. SynchroPharmX Hub makes learning easy. Overview Section 1: Introduction to the basic principles of radiopharmaceuticals Lecture 1 Basic principles of radiopharmaceuticals Lecture 2 Radithor and the man with the crumbled bones! Section 2: Categories of radiopharmaceuticals Lecture 3 Ready to use radiopharmaceuticals (Part 1) Lecture 4 Ready to use radiopharmaceuticals (Part 2) Lecture 5 Radiopharmaceutical in the form of instant kit Lecture 6 Radiopharmaceutical kit requiring heating Lecture 7 Radiopharmaceutical kit requiring significant manipulation Lecture 8 White blood cells labeling kit Section 3: SPECT and PET scanners and radiopharmaceuticals Lecture 9 Principles of radiation detection: SPECT scanner (Part 1) Lecture 10 Principles of radiation detection: SPECT scanner (Part 2) Lecture 11 Principles of radiation detection: PET scanner Lecture 12 Differences between SPECT and PET radionuclides Lecture 13 References The course is intended to provide a basic level of knowledge on the principles, categories of radiopharmaceuticals and the differences between SPECT and PET scanners and radiopharmaceuticals Homepage https://www.udemy.com/course/learning-basics-of-radiopharmaceuticals/ Rapidgator https://rg.to/file/d1ab8fcb5e13691a62f585e69a2b3299/eqoys.Learning.Basics.Of.Radiopharmaceuticals.part1.rar.html https://rg.to/file/d791892f8dce81530759ffbf477063ad/eqoys.Learning.Basics.Of.Radiopharmaceuticals.part2.rar.html Fikper Free Download https://fikper.com/o8oBD0tbjv/eqoys.Learning.Basics.Of.Radiopharmaceuticals.part1.rar https://fikper.com/aWHN0kvuKq/eqoys.Learning.Basics.Of.Radiopharmaceuticals.part2.rar No Password - Links are Interchangeable

Free Download Mastering AI From Machine Learning to Automation Published 10/2024 Created by Ndiaga Fall MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 53 Lectures ( 6h 37m ) | Size: 4.5 GB AI, Machine Learning, Reinforcement Learning, Robotics, Automation What you'll learn: Automation Artificial intelligence Machine Learning Field Knowlegde Robotics Reinforcement Learning Requirements: No prior experience in Artificial Intelligence is required Description: Unlock the power of Artificial Intelligence (AI) and gain hands-on experience with cutting-edge technologies like Machine Learning, Reinforcement Learning, Robotics, Automation, and Natural Language Processing (NLP). This course is designed to take you from AI fundamentals to advanced applications, empowering you to build intelligent systems and solve real-world challenges.What You Will Learn:Artificial Intelligence Foundations: Understand the core principles of AI and how it's revolutionizing industries like healthcare, finance, and robotics.Machine Learning (ML): Dive into supervised and unsupervised learning, build predictive models, and master techniques like decision trees, neural networks, and deep learning.Reinforcement Learning (RL): Explore how intelligent agents make decisions through trial and error in dynamic environments, using algorithms that optimize long-term success.Robotics & Automation: Discover how AI-driven robots are transforming automation processes and how machine learning is enabling robots to interact with their surroundings in real time.Natural Language Processing (NLP): Learn to build models that understand, generate, and respond to human language, using techniques such as sentiment analysis, text generation, and speech recognition.Real-World Applications: Implement AI solutions for automation, decision-making, and optimization tasks in various industries, and explore the future potential of AI in robotics and beyond.Why Take This Course? Whether you're an aspiring data scientist, an AI enthusiast, or a professional looking to automate processes, this course offers a complete roadmap to mastering AI. By the end of the course, you will have the skills to build intelligent systems that can learn, adapt, and interact with the world around them.Join us today and step into the future of AI and robotics! Who this course is for: Beginners curious about Artificial Intelligence Homepage https://www.udemy.com/course/mastering-ai-from-machine-learning-to-automation/ Rapidgator https://rg.to/file/460a6233b268963abd3bd4a9fe60e766/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part1.rar.html https://rg.to/file/9463bab2d2169ebe876e3e0945e26942/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part2.rar.html https://rg.to/file/9c1df9307a52b94723c3e2d4d9931b76/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part3.rar.html https://rg.to/file/9f0b52b9071fcccc6f12ad9999a2ff5b/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part4.rar.html https://rg.to/file/af3cdb3c5c4b3a32b6e8a3f4c448eef5/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part5.rar.html Fikper Free Download https://fikper.com/JvlEWN1jIB/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part1.rar https://fikper.com/62BOmMn010/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part2.rar https://fikper.com/4oH3PqPVuv/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part3.rar https://fikper.com/Xtm7teNRik/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part4.rar https://fikper.com/v9QvlBDT49/opikl.Mastering.AI..From.Machine.Learning.to.Automation.part5.rar No Password - Links are Interchangeable

Free Download MQL5 MACHINE LEARNING Linear Regression for Algo Trading Published 10/2024 Created by Latvian Trading Solutions MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 25 Lectures ( 3h 42m ) | Size: 2 GB A complete guide to developing linear regression based models for algorithmic trading in MQL5 What you'll learn: The concept of Linear Regression and its application in Algorithmic Trading How to Develop a Linear Regression model on a spread sheet How to code a Linear Regression model Indicator in MQL5 How to develop a Linear Regression Strategy and code an Expert advisor in MQL5 Requirements: Basics of MQL5 Description: Simple linear regression is a statistical method used to model the relationship between two variables: an independent variable (x) and a dependent variable (y). It assumes a linear relationship between the two variables and aims to find the best-fitting straight line that represents this relationship.The equation for a simple linear regression model is:y = ax + bWhere:y is the dependent variable (the variable we want to predict).x is the independent variable (the variable used to make predictions).a is the slope of the line, representing the rate of change of y with respect to x.b is the y-intercept, representing the value of y when x is zero.While simple linear regression is a statistical technique, it can also be considered as a machine learning algorithm. In machine learning, the goal is to build models that can learn from data and make predictions. Linear regression fits this framework because it learns the relationship between x and y from a given dataset and uses this learned relationship to make predictions for new data points. As neural networks learn the best non-linear relationships between data by finding the weights that best fit the data, linear regression aims to find the best values of a and b that best describe the linear relationship between variables.In this course, our aim is to build a linear regression model in mql5 that seeks to predict the closing prices of a currency pair given its specific bar index. We shall start by creating a linear regression model on a spread sheet to basically explain the calculations involved in creating a linear regression model. We shall then develop our linear regression model as an mql5 indicator by coding it using the mql5 programming language. After that, we shall develop our trading strategy as an mql5 expert advisor coded using the mql5 algorithmic trading language. We shall use the linear regression model we created as an indicator to analyze data and find patterns we can use to profit from the market. We shall base our trading logic on the fact that if price goes beyond one or two standard deviations from its predicted or expected price, it has to reverse and go back to its expected price. Hence our strategy will be a mean reversion type of strategy.For those that are still finding their way with MQL5, as long as you understand the basics of MQL5, this course is for you. We will patiently guide you through every step of the strategy development process and walk you through every line of code we shall craft. Hopefully, by the end of the course, you will have gained the necessary skills to code similar models and trading strategies and be able to appreciate how linear regression models can be an asset in developing your own trading ideas based on the ideas that shared in this course.So hit hard on that enroll button now and join me in this incredible journey of coding a linear regression model using the mql5 algorithmic trading language. Who this course is for: Anyone willing to learn about the applications of Linear Regression in Market analysis and timeseries forecasting Homepage https://www.udemy.com/course/mql5-machine-learning-linear-regression-for-algo-trading/ Rapidgator https://rg.to/file/630d36f1b4288747a471e52674d9d4dd/tckwc.MQL5.MACHINE.LEARNING.Linear.Regression.for.Algo.Trading.part1.rar.html https://rg.to/file/7645de1e68ac2dcf4f2b70fa72700e70/tckwc.MQL5.MACHINE.LEARNING.Linear.Regression.for.Algo.Trading.part2.rar.html https://rg.to/file/482c3aed89c0666e8b54135282d626d2/tckwc.MQL5.MACHINE.LEARNING.Linear.Regression.for.Algo.Trading.part3.rar.html Fikper Free Download https://fikper.com/1HmmIr9mbW/tckwc.MQL5.MACHINE.LEARNING.Linear.Regression.for.Algo.Trading.part1.rar https://fikper.com/R3AmHQhj0Z/tckwc.MQL5.MACHINE.LEARNING.Linear.Regression.for.Algo.Trading.part2.rar https://fikper.com/4wDuaEE6tI/tckwc.MQL5.MACHINE.LEARNING.Linear.Regression.for.Algo.Trading.part3.rar No Password - Links are Interchangeable

Free Download Automating Learning And Development Within The Organisation Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.01 GB | Duration: 1h 10m Streamline Employee Training What you'll learn Identify the LMS platform to automate training and development Implement instructional design principles when creating online module Use tools for creating digital content Apply for curriculum transfer to digital platforms Learn how to automate learning and development within the organisation Requirements Learners must assume roles related to training, human resources, or organisational development Learners may need a background in human resources, organisational development, or a related field Understanding of organisational structures, employee roles, and performance management may be beneficial Tech-savvy Description Training and education are evolving rapidly, driven by the impact of the Covid-19 pandemic and changing learner demographics. Technological advancements like adaptive learning, automated interventions, dynamic digital content, and mobile technology have opened up new possibilities for training and development, especially for Generation Y and Generation Z.In Learning and Development (L&D), automation uses technology to streamline tasks such as content creation, training delivery, and assessments. It allows for instant feedback, personalised learning paths, and data-driven analytics, leading to greater efficiency, scalability, and personalised learning experiences. This, in turn, enhances both learning outcomes and organisational performance.A Learning Management System (LMS) is software designed to manage, document, track, report, automate, and deliver educational courses or training programs. Beyond automating the training process, an LMS accelerates the learning experience, making it easier for learners to access and complete their training.Automation in L&D improves the efficiency, effectiveness, and scalability of employee training. Tools like software platforms, artificial intelligence, and data analytics optimise content creation, training delivery, and performance tracking. For instance, LMS platforms can automate tasks such as administration, documentation, and reporting, while AI tools can personalise training content to meet individual employee needs. Automation also enables employees to access training materials on-demand, helping them stay current with new skills.Moreover, automation allows training programs to scale effectively, maintaining consistent quality across larger groups of employees, regardless of location. This is particularly valuable for global companies, as it saves time and resources compared to traditional in-person training methods. Overall, automation helps organisations develop their workforce more efficiently, supporting business goals while boosting engagement and performance. Overview Section 1: Course Overview and Introduction Lecture 1 Course Overview Lecture 2 Introduction to Automation in Learning and Development Section 2: Using a Learning Management System (LMS) in Creating Digital Content Lecture 3 LMS Features, Common LMS Platform, Selecting an LMS Section 3: Instructional Design Principles in Developing E-Learning Modules Lecture 4 Instructional Design in E-Learning, The ADDIE Model Section 4: Tools Available for Digital Contents Lecture 5 Multimedia Tools Section 5: E-Learning Content Development Lecture 6 Translating TNA Findings into Training Objectives, Creating a Storyboard Section 6: Multimedia Integration in E-Learning Content Development Lecture 7 Convert Training Materials to Digital Format, Create Basic Videos Section 7: Example of Automating Learning and Development Lecture 8 Automating Learning and Development in Five Steps Section 8: Case Study Lecture 9 Success Story Section 9: Summary of Key Learnings and Evaluation Lecture 10 Summary of Key Learnings Lecture 11 Evaluation HR Personnel,Training Coordinator,Trainers,Facilitators Homepage https://www.udemy.com/course/automating-learning-and-development/ Rapidgator https://rg.to/file/f8229b514474de21061ac13794ed4c93/lbxso.Automating.Learning.And.Development.Within.The.Organisation.part1.rar.html https://rg.to/file/ec0c37fde097c1a50ed7549c394e793c/lbxso.Automating.Learning.And.Development.Within.The.Organisation.part2.rar.html Fikper Free Download https://fikper.com/T6VrTl4FnT/lbxso.Automating.Learning.And.Development.Within.The.Organisation.part1.rar https://fikper.com/HDJoO8hFa2/lbxso.Automating.Learning.And.Development.Within.The.Organisation.part2.rar No Password - Links are Interchangeable

Free Download Learning Path - CompTIA SecurityX / CASP+ (CAS-005) Exam Date: November 2024 Released 10/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 8h 31m | Size: 2 GB CompTIA SecurityX / CASP+ (CompTIA Advanced Security Practitioner) is a globally recognized certification that validates your mastery of advanced cybersecurity concepts and techniques. Our course is specifically tailored to help you understand and navigate the SecurityX / CASP+ exam objectives, ensuring you're fully prepared to ace the certification exam and demonstrate your proficiency to employers. Homepage https://app.pluralsight.com/paths/certificate/comptia-securityx-casp-cas-005 TakeFile https://takefile.link/1q7jgcdtu65e/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part2.rar.html https://takefile.link/2619bkvogq0m/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part1.rar.html https://takefile.link/7d3jov7ho265/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part3.rar.html Rapidgator https://rg.to/file/6cdc3fd71f2c88bf4d92f42d4ab2274f/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part2.rar.html https://rg.to/file/c7dcd90a56190e3b2c39c801431e3ce7/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part3.rar.html https://rg.to/file/de2d5fc097ccec1f9b0a6823587bfe53/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part1.rar.html Fikper Free Download https://fikper.com/7peVU0lbVg/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part1.rar.html https://fikper.com/rVyNRsmpVl/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part3.rar.html https://fikper.com/veUfmj4F2A/fnmif.Learning.Path..CompTIA.SecurityX..CASP.CAS005.Exam.Date.November.2024.part2.rar.html No Password - Links are Interchangeable

Free Download Re-Learning Coding - Masters Journey To Mastering Basics Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.74 GB | Duration: 1h 40m Join me as we re-discover coding fundamentals, tackle common challenges, and build coding confidence-one step at a time. What you'll learn Basic Syntax: Understand how to write and run Python code, including variables, data types, and basic operations. Control Structures: Learn to use conditionals and loops to control the flow of your programs, making decisions based on user input. Functions: Discover how to define and call functions, allowing you to organize your code and reuse logic effectively. Simple Projects: Build hands-on projects like a calculator and a number-guessing game to reinforce your coding skills and boost confidence. Requirements Familiarity with using a computer, including navigating files and folders, using web browsers, and installing software. A positive attitude and an eagerness to learn coding concepts, along with patience for troubleshooting and problem-solving. Understanding of basic math concepts, such as addition, subtraction, multiplication, and division, will be helpful. Description Welcome to "Re-learning Coding: Master's Journey to Mastering Basics." In this course, we will explore the fundamentals of programming in a supportive and engaging way, making coding accessible to everyone. Whether you're starting from scratch or refreshing your skills, this course is designed with you in mind.Throughout our journey together, we'll cover essential topics like variables, data types, control structures, loops, and functions. Each concept will be presented in a clear, easy-to-understand manner, ensuring that you grasp the material without feeling overwhelmed. Learning to code doesn't have to be intimidating; with the right guidance, it can be enjoyable!One of the unique aspects of this course is the emphasis on hands-on learning. You won't just be passively watching videos; you'll be actively writing code and building small projects. By the end of the course, you'll have created practical applications, such as a basic calculator and a number-guessing game. These projects will not only solidify your understanding but also provide you with tangible examples of your skills.Mistakes are a natural part of the learning process, and I'll show you how to troubleshoot and debug your code effectively. This approach encourages a growth mindset, empowering you to see challenges as opportunities for improvement.This course is perfect for complete beginners, returning learners, students, professionals, and anyone looking to enhance their skills or explore coding as a new hobby. By the end of our journey, you'll have the confidence to tackle coding challenges and continue your programming journey independently. Join us, and let's unlock the world of coding together! Overview Section 1: Welcome to Our Coding Journey Lecture 1 Introduction: Who I Am and Why We're Learning Together Lecture 2 How This Course is Different: Let's Keep It Real and Fun Lecture 3 What You'll Need to Get Started Section 2: Back to the Basics-What is Coding? Lecture 4 What is Programming? Understanding the Big Picture Lecture 5 Setting Up Your Coding Environment Lecture 6 Installing Python and Pycharm Lecture 7 First Line of Code: Hello World! Section 3: Variables and Data Types Lecture 8 What Are Variables? Lecture 9 Understanding Data Types: Strings, Integers, and More Lecture 10 Hands-On: Play Around with Variables Section 4: Conditionals-Making Decisions in Code Lecture 11 If, Else, and Else If: Making Choices in Code Lecture 12 Practice: Write Your First Conditional Statements Section 5: Loops-Doing Things Repeatedly Lecture 13 For Loops: Automating Repeated Tasks Lecture 14 While Loops: Repeat Until. Lecture 15 Challenge: Create a Simple Program with Loops Section 6: Functions-Creating Reusable Code Lecture 16 What are Functions and Why Use Them? Lecture 17 Writing Your First Function Lecture 18 Writing Your First Function Section 7: Debugging and Problem Lecture 19 Don't Panic! Debugging Common Errors Section 8: Projects-Let's Build Something Cool! Lecture 20 Mini Project: Build a Simple Calculator Lecture 21 Mini Project: Create a Guess the Number Game Section 9: Wrapping It Up-What's Next? Lecture 22 Congratulations! Reflecting on How Far We've Come Lecture 23 Thank You & Stay in Touch Complete Beginners: Individuals with no prior coding experience who want to learn the basics of programming.,Returning Learners: Those who have coded in the past but need a refresher on fundamental concepts and skills.,Students and Professionals: Anyone looking to enhance their skills for school projects, career advancement, or personal growth in technology. 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Free Download Mastering Machine Learning From Basics To Breakthroughs Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 918.11 MB | Duration: 3h 38m Machine Learning, Supervised Learning, Unsupervised Learning, Regression, Classification, Clustering, Markov Models What you'll learn Explore the fundamental mathematical concepts of machine learning algorithms Apply linear machine learning models to perform regression and classification Utilize mixture models to group similar data items Develop machine learning models for time-series data prediction Design ensemble learning models using various machine learning algorithms Requirements Foundations of Mathematics and Algorithms Description This Machine Learning course offers a comprehensive introduction to the core concepts, algorithms, and techniques that form the foundation of modern machine learning. Designed to focus on theory rather than hands-on coding, the course covers essential topics such as supervised and unsupervised learning, regression, classification, clustering, and dimensionality reduction. Learners will explore how these algorithms work and gain a deep understanding of their applications across various domains.The course emphasizes theoretical knowledge, providing a solid grounding in critical concepts such as model evaluation, bias-variance trade-offs, overfitting, underfitting, and regularization. Additionally, it covers essential mathematical foundations like linear algebra, probability, statistics, and optimization techniques, ensuring learners are equipped to grasp the inner workings of machine learning models.Ideal for students, professionals, and enthusiasts with a basic understanding of mathematics and programming, this course is tailored for those looking to develop a strong conceptual understanding of machine learning without engaging in hands-on implementation. It serves as an excellent foundation for future learning and practical applications, enabling learners to assess model performance, interpret results, and understand the theoretical basis of machine learning solutions.By the end of the course, parti[beeep]nts will be well-prepared to dive deeper into machine learning or apply their knowledge in data-driven fields, without requiring programming or software usage. Overview Section 1: Introduction Lecture 1 Introduction to Machine Learning Lecture 2 Types of Machine Learning Lecture 3 Polynomial Curve Fitting Lecture 4 Probability Lecture 5 Total Probability, Bayes Rule and Conditional Independence Lecture 6 Random Variables and Probability Distribution Lecture 7 Expectation, Variance, Covariance and Quantiles Section 2: Linear Models for Regression Lecture 8 Maximum Likelihood Estimation Lecture 9 Least Squares Method Lecture 10 Robust Regression Lecture 11 Ridge Regression Lecture 12 Bayesian Linear Regression Lecture 13 Linear models for classification::Discriminant Functions Lecture 14 Probabilistic Discriminative and Generative Models Lecture 15 Logistic Regression Lecture 16 Bayesian Logistic Regression Lecture 17 Kernel Functions Lecture 18 Kernel Trick Lecture 19 Support Vector Machine Section 3: Mixture Models and EM Lecture 20 K-means clustering Lecture 21 Mixtures of Gaussians Lecture 22 EM for Gaussian Mixture Models Lecture 23 PCA, Choosing the number of latent dimensions Lecture 24 Hierarchial clustering Students, data scientists and engineers seeking to solve data-driven problems through predictive modeling Homepage https://www.udemy.com/course/mastering-machine-learning-from-basics-to-breakthroughs/ Rapidgator https://rg.to/file/7a1c1299ff4b931eddf50e6b453b5dbb/ddbol.Mastering.Machine.Learning.From.Basics.To.Breakthroughs.rar.html Fikper Free Download https://fikper.com/46pB4R63M3/ddbol.Mastering.Machine.Learning.From.Basics.To.Breakthroughs.rar.html No Password - Links are Interchangeable

Free Download Learning Path - Maximizing Triggers in SQL Server Development Last updated 4/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 49 Lessons ( 3h ) | Size: 555 MB This learning path provides comprehensive insights into the creation and utilization of triggers in SQL Server This learning path provides comprehensive insights into the creation and utilization of triggers in SQL Server. From introductory concepts to designing effective Data Manipulation Language (DML) triggers, and advancing to optimization and troubleshooting of complex triggers, learners will discover how to combine triggers with stored procedures for enhanced database functionality. What You Will Learn The basics of triggers in SQL Server How to design effective DML triggers in SQL Server How to optimize and troubleshoot advanced SQL Server triggers How to approach triggers and stored procedures together in SQL Server Experience Learners interested in this path should have a basic understanding of SQL Server and familiarity with writing SQL queries. Homepage https://www.pluralsight.com/paths/maximizing-triggers-in-sql-server-development TakeFile https://takefile.link/28rmbnn7w87v/lwrhg.Learning.Path..Maximizing.Triggers.in.SQL.Server.Development.rar.html Rapidgator https://rg.to/file/6b65826b31c91d29f979ae7349ace1aa/lwrhg.Learning.Path..Maximizing.Triggers.in.SQL.Server.Development.rar.html Fikper Free Download https://fikper.com/D5g1QbBlTj/lwrhg.Learning.Path..Maximizing.Triggers.in.SQL.Server.Development.rar.html No Password - Links are Interchangeable

Free Download Learning Path - Enhancing SQL Server Query Efficiency Last updated 5/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 48 Lessons ( 2h 38m ) | Size: 477 MB This learning path is designed for those seeking to leverage SQL Server for advanced data analysis and trend identification This learning path is designed for those seeking to leverage SQL Server for advanced data analysis and trend identification. It starts with the basics of trend analysis, then progresses to handling dynamic data patterns and implementing predictive analysis techniques. Learners will also explore how to combine SQL Server with Power BI for effective data visualization, and how to perform real-time trend analysis. What You Will Learn How to perform trend analysis with SQL Server How to work with dynamic data patterns in SQL Server How to perform predictive analysis with SQL Server How to visualize data trends with SQL Server and Power BI How to perform real-time trend analysis with SQL Server Experience Learners interested in this path should have a foundational understanding of SQL Server, basic data analysis principles, and familiarity with SQL queries. Foundational knowledge of Power BI is also recommended. Homepage https://www.pluralsight.com/paths/enhancing-sql-server-query-efficiency TakeFile https://takefile.link/79v0peep9yuz/dmgdz.Learning.Path..Enhancing.SQL.Server.Query.Efficiency.rar.html Rapidgator https://rg.to/file/0e157abba02b66e94d44faddfebbe34a/dmgdz.Learning.Path..Enhancing.SQL.Server.Query.Efficiency.rar.html Fikper Free Download https://fikper.com/aq2SJsuZbL/dmgdz.Learning.Path..Enhancing.SQL.Server.Query.Efficiency.rar.html No Password - Links are Interchangeable

Free Download Learning Path - Crafting Functions and Procedures in SQL Server Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 49 Lessons ( 2h 30m ) | Size: 467 MB This learning path is aimed at developers and database administrators who want to build expertise in creating, managing, and optimizing functions and stored procedures within SQL Server. This learning path is aimed at developers and database administrators who want to build expertise in creating, managing, and optimizing functions and stored procedures within SQL Server. Starting with the fundamentals of SQL Server functions, learners will go through the construction of their first functions, and then advance to complex scenarios that focus on performance and practical application. The path also helps learners master stored procedures, emphasizing optimization techniques, best practices for performance enhancement, and strategies for seamlessly integrating functions and procedures into SQL Server workflows. What You Will Learn Fundamentals of SQL Server functions Advanced functions in SQL Server How to master stored procedures in SQL Server How to optimize procedures in SQL Server How to integrate functions and procedures in SQL Server workflows Experience Learners interested in this path should have a solid understanding of SQL Server basics, including familiarity with T-SQL syntax and the fundamentals of database design and operations. Knowledge of basic programming concepts in SQL is also essential to fully grasp the advanced topics covered in this learning path. Homepage https://www.pluralsight.com/paths/crafting-functions-and-procedures-in-sql-server TakeFile https://takefile.link/k0p4t1r3erfg/bmjhd.Learning.Path..Crafting.Functions.and.Procedures.in.SQL.Server.rar.html Rapidgator https://rg.to/file/5c1557def873cbf3a54b64fe7848f83a/bmjhd.Learning.Path..Crafting.Functions.and.Procedures.in.SQL.Server.rar.html Fikper Free Download https://fikper.com/6KxxG9Gwt9/bmjhd.Learning.Path..Crafting.Functions.and.Procedures.in.SQL.Server.rar.html No Password - Links are Interchangeable

Free Download Introduction to AI and Machine Learning on Google Cloud Duration: 2h 50m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 378 MB Genre: eLearning | Language: English This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects. It explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions. It aims to help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises. Homepage https://www.pluralsight.com/courses/introduction-ai-machine-learning-google-cloud TakeFile https://takefile.link/mt7ylysqlg62/clutv.Introduction.to.AI.and.Machine.Learning.on.Google.Cloud.rar.html Rapidgator https://rg.to/file/3bb6644cc7ee9b81d506bb54bd54f855/clutv.Introduction.to.AI.and.Machine.Learning.on.Google.Cloud.rar.html Fikper Free Download https://fikper.com/L2Wl0zcgJY/clutv.Introduction.to.AI.and.Machine.Learning.on.Google.Cloud.rar.html No Password - Links are Interchangeable

epub | 9.51 MB | English| Isbn:9781351216449 | Author: Ellen J. Brooks | Year: 2017 Description: Category:Education, Education - General & Miscellaneous, Education - Miscellaneous Topics https://ddownload.com/4nw4t364pa8o https://rapidgator.net/file/ed22768e9c95e15f2ef5145a396eca7e/ https://turbobit.net/uv8iw2r3nyu4.html

Free Download Hands-On Machine Learning with Python - Real Projects Published 9/2024 Created by TechJedi LLP MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 39 Lectures ( 3h 4m ) | Size: 2.2 GB Master Machine Learning with Python: Build, Train & Deploy Models with Real-World Projects What you'll learn: Implement Machine Learning algorithms in Python using libraries like scikit-learn and TensorFlow. Preprocess and analyze datasets to build predictive models. Evaluate model performance and select the best algorithms for various problems. Develop and deploy real-world machine learning applications from scratch. Requirements: Basic knowledge of Python programming is helpful but not mandatory. No prior experience in Machine Learning required - we'll start from the basics. A computer with Python and essential libraries installed (instructions provided in the course). Curiosity and a willingness to learn - the course is designed for all levels! Description: Dive into the exciting world of Machine Learning with our comprehensive course designed for aspiring data scientists, Python developers, and AI enthusiasts. This course will equip you with the essential skills and practical knowledge to harness the power of Machine Learning using Python.You will begin with the fundamentals of Machine Learning, exploring its definition, types, and workflow, while setting up your Python environment. As you progress, you'll delve into data preprocessing techniques to ensure your datasets are clean and ready for analysis.The course covers supervised and unsupervised learning algorithms, including Linear Regression, Decision Trees, K-Means Clustering, and Prin[beeep]l Component Analysis. Each section features hands-on projects that reinforce your understanding and application of these concepts in Python.You will learn to evaluate and select models using metrics and hyperparameter tuning, ensuring your solutions are both effective and efficient. Our in-depth exploration of Deep Learning with TensorFlow will introduce you to neural networks and advanced architectures like Convolutional Neural Networks (CNN).Additionally, you'll discover the essentials of Natural Language Processing (NLP), mastering text preprocessing and word embeddings to extract insights from textual data. As you approach the course's conclusion, you will gain valuable skills in model deployment, learning how to create web applications using Flask and ensure your models are production-ready.Cap off your learning journey with a real-world capstone project where you will apply everything you've learned in an end-to-end Machine Learning workflow, culminating in a presentation and peer review.Whether you are a beginner eager to enter the field or a professional looking to enhance your skill set, this course provides the tools and knowledge necessary to succeed in the dynamic landscape of Machine Learning. Join us and take the first step toward mastering Machine Learning in Python today! Who this course is for: Beginners interested in Machine Learning who want to learn through hands-on projects. Python developers looking to expand their skills in data science and machine learning. Data analysts and statisticians eager to apply machine learning techniques to real-world problems. Anyone curious about AI and Machine Learning who wants to build practical models without prior experience. Homepage https://www.udemy.com/course/hands-on-machine-learning-with-python-real-projects/ Rapidgator https://rg.to/file/02d6ffc63e6ece2a4e12c2e90128cedb/ybabz.HandsOn.Machine.Learning.with.Python.Real.Projects.part3.rar.html https://rg.to/file/338df430412602fc1fc32a7258664316/ybabz.HandsOn.Machine.Learning.with.Python.Real.Projects.part2.rar.html https://rg.to/file/42436adc219bc9af71d070f5eeaf0cdb/ybabz.HandsOn.Machine.Learning.with.Python.Real.Projects.part1.rar.html Fikper Free Download https://fikper.com/KcdzKXVqlA/ybabz.HandsOn.Machine.Learning.with.Python.Real.Projects.part2.rar.html https://fikper.com/uVJ7SQr1t6/ybabz.HandsOn.Machine.Learning.with.Python.Real.Projects.part3.rar.html https://fikper.com/xoPGTfFCF2/ybabz.HandsOn.Machine.Learning.with.Python.Real.Projects.part1.rar.html No Password - Links are Interchangeable

Free Download Aws Workshops - Hands-On Learning With Demos Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.97 GB | Duration: 3h 25m Quick Workshops! What you'll learn Hands-on experience with AWS S3 Hands-on experience with AWS VPC Creation Hands-on experience with AWS IAM Hands-on experience with other AWS Services Requirements Basic understanding of IT concepts and networking No prior AWS experience required Description Welcome to the AWS Hands-On Labs and Demos course! This course is designed to provide you with practical, hands-on experience with Amazon Web Services (AWS). Whether you're a beginner looking to understand the basics or an experienced professional aiming to deepen your knowledge, this course offers a comprehensive learning experience.Course Objectives:Gain a solid understanding of core AWS services and their applications.Learn how to set up and manage AWS environments.Develop skills to deploy, manage, and scale applications on AWS.Explore real-world scenarios through workshop demos.Course Highlights:Workshop-Style Learning: Engage in step-by-step labs that guide you through various AWS services, including EC2, S3, VPC, and more.Real-World Scenarios: Apply your knowledge to real-world scenarios, helping you understand how AWS services are used in practical situations.Workshops: Learn from Workshops developed by AWS-certified instructors with extensive industry experience.Resources and Scripts: Access resources and scripts used in demos to practice and reinforce your learning.Certification Preparation: This course also helps you prepare for AWS certification exams by covering fundamental topics.Who Should Enroll:IT professionals looking to enhance their cloud computing skills.Developers and engineers interested in deploying applications on AWS.Students and beginners who want to start a career in cloud computing.Anyone preparing for AWS certification exams.Prerequisites:Basic understanding of IT concepts and networking.No prior AWS experience required. Overview Section 1: Introduction Lecture 1 Welcome 2 Workshops! Section 2: Workshop #01 - AWS Signup & Setting Billing Alerts Lecture 2 Objectives Lecture 3 What do we need? Lecture 4 Workshop Activity Lecture 5 Clean Up & Conclusion Section 3: Workshop #02 - Introduction to AWS Management Console Lecture 6 Objectives Lecture 7 Workshop Activity #1 : Exploring the AWS Management Console Lecture 8 Clean Up & Conclusion Section 4: Workshop #03 - Understanding the default VPC Lecture 9 Objectives Lecture 10 Workshop Activity Lecture 11 Clean Up & Conclusion Section 5: Workshop #04 - Create EC2 instances and connect remotely Lecture 12 Objectives Lecture 13 Workshop Introduction Lecture 14 Workshop Activity Section 6: Workshop #05 - Create EC2 instance and install nginx Lecture 15 Objectives Lecture 16 What do we need? Lecture 17 Lab Resources Lecture 18 Workshop Introduction Lecture 19 Workshop Activity Lecture 20 Clean Up! Lecture 21 Learning Recommendations Section 7: Workshop #06 - Launching EC2 Spot Instances Lecture 22 Objectives Lecture 23 Workshop Introduction Lecture 24 Workshop Solution Lecture 25 Clean Up! Lecture 26 Learning Recommendations Section 8: Workshop #07 - Managing Permissions using IAM Lecture 27 Objectives Lecture 28 Workshop Introduction Lecture 29 Workshop Solution Lecture 30 Clean Up! Lecture 31 Learning Recommendations Section 9: Workshop #08 - Creating Amazon S3 bucket and enabling Public Access Lecture 32 Workshop Introduction & Architecture Diagrams Lecture 33 Lab Resources (Sample Files, Sample Code, etc.) Lecture 34 Workshop Solution Lecture 35 Clean Up! Lecture 36 Learning Recommendations Section 10: Workshop #09 - Hosting a static website using Amazon S3 Lecture 37 Workshop Introduction Lecture 38 Workshop Solution Lecture 39 Workshop Resources Lecture 40 Clean Up! Lecture 41 Learning Recommendations Section 11: Workshop #10 - Configure Amazon S3 Buckets for Versioning & Cross-Region Replica Lecture 42 Workshop Introduction & Architecture Diagrams Lecture 43 Workshop Resources Lecture 44 Workshop Solution Lecture 45 Clean Up! Lecture 46 Learning Recommendations IT professionals looking to enhance their cloud computing skills.,Developers and engineers interested in deploying applications on AWS.,Students and beginners who want to start a career in cloud computing.,Anyone preparing for AWS certification exams. 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Free Download Udemy - Deep Learning - A Complete User Guide Published 9/2024 Created by Dr. Rahul Mapari MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 21 Lectures ( 6h 24m ) | Size: 1.91 GB Machine Learning, Deep Learning, NLP What you'll learn: To Clear the Fundamentals of Machine Learning To Explain the Machine Learning Algorithms To Clear the Concepts of Artificial Neural Network (ANN) and Convolutional Neural Networks (CNN) To Clear the Concepts of Natural Language Processing (NLP) and its Algorithms To Provide Hands on Experience by Solving Real Time Problems of ANN, CNN and Deep Neural Networks Requirements: No prerequisites, everything will be clear in this course. Description: This comprehensive course on deep learning is designed to provide parti[beeep]nts with a thorough understanding of the principles, techniques, and applications of machine learning and deep learning. Whether you are a beginner looking to enter the field of artificial intelligence or an experienced professional aiming to enhance your skills, this course covers a wide range of topics to cater to various levels of expertise. This course will clear the basic concepts of machine learning and deep learning. Mathematical intuitions of linear and logistic regression, machine learning algorithms like decision tree, random forest, naive bayes, support vector machine etc., will be cover. Overfitting, under fitting concepts and their techniques of avoidance like dropout, L1, L2 regularization, early stopping is also highlight during this course. This course also covers the complete understanding of Artificial Neural Network (ANN), Convolutional Neural Network (CNN), recurrent neural network (RNN), Dated Recurrent Units (GRU) and Generative Adversarial Network (GAN) techniques. The natural language processing application are also the part of this course. At the end hands-on practice on real time case studies on linear regression, logistic regression, decision tree, random forest, naive bayes, support vector machine, ANN, CNN, RNN, GAN will be discussed. By the end of this course, parti[beeep]nts will have gained a solid foundation in deep learning, enabling them to apply these techniques to various domains and stay abreast of the rapidly evolving field. Whether you are looking to kickstart a career in AI or enhance your current skills, this course provides a comprehensive and practical guide to deep learning. Who this course is for: Beginners in AI, ML, and Deep Learning Homepage https://www.udemy.com/course/deep-learning-a-complete-user-guide/ Rapidgator https://rg.to/file/35e414a566a7e693c06e45bb5cd72cd2/ihzti.Deep.Learning..A.Complete.User.Guide.part1.rar.html https://rg.to/file/d88075742105df7d2c516b3216e00443/ihzti.Deep.Learning..A.Complete.User.Guide.part2.rar.html Fikper Free Download https://fikper.com/WIsa4KWxgV/ihzti.Deep.Learning..A.Complete.User.Guide.part1.rar.html https://fikper.com/z2qDspLLmK/ihzti.Deep.Learning..A.Complete.User.Guide.part2.rar.html No Password - Links are Interchangeable

Free Download TensorFlow for Deep Learning - Build AI Models Like a Pro Published 9/2024 Created by Deepak Rai MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 13 Lectures ( 2h 31m ) | Size: 1.93 GB Master the Art of Building and Deploying Advanced AI Models Using TensorFlow - From Beginner to Expert What you'll learn: Master TensorFlow basics, from setup to building and deploying deep learning models. Create neural networks for tasks like image recognition and text generation Build advanced models like CNNs, RNNs, and LSTMs using TensorFlow. Optimize model performance for faster, more accurate AI solutions. Learn how to deploy AI models into production environments efficiently. Requirements: Requirements and Prerequisites for Taking This Course: Basic Python knowledge: Familiarity with Python programming is recommended as we'll use Python to implement TensorFlow models. Fundamental understanding of machine learning: Prior knowledge of basic machine learning concepts like supervised learning and classification will be helpful. Interest in AI and deep learning: No prior deep learning or TensorFlow experience is required, but a strong interest in learning AI technologies is key. A computer with internet access: You'll need a computer to install TensorFlow, run code, and follow along with the hands-on exercises. Eagerness to learn and apply new skills: This course is designed for students ready to dive into practical deep learning with real-world applications. This ensures students are prepared while also welcoming beginners with the basics covered during the course. Description: Unlock the full potential of deep learning with TensorFlow, the leading open-source framework for building cutting-edge AI models. In this hands-on course, you'll learn how to master TensorFlow and create powerful artificial intelligence solutions, from basic concepts to advanced applications.Whether you're a beginner looking to dive into deep learning or an experienced developer aiming to sharpen your skills, this course is designed for you. With easy-to-follow lessons, real-world projects, and expert guidance, you'll build, train, and deploy neural networks for image recognition, natural language processing, and more.Key Highlights:Learn TensorFlow step-by-step - from installation to deploying AI models.Build your first neural network and progress to advanced architectures like CNNs, RNNs, and LSTMs.Hands-on projects that focus on practical applications of AI and machine learning.Explore real-world use cases like image classification, text generation, and predictive analytics.Perfect for beginners and experienced developers alike, no prior TensorFlow experience required.What You Will Learn:Deep learning fundamentals and how they apply to AI development.How to implement state-of-the-art models using TensorFlow.Techniques to optimize model performance and handle large datasets.How to deploy your AI models to production environments.Why This Course?TensorFlow powers the world's most advanced AI systems, and this course equips you with the skills to join this rapidly growing industry. With comprehensive resources and expert instruction, you'll be building AI models like a pro in no time.Enroll today and take the first step toward becoming a TensorFlow expert in deep learning! Who this course is for: Who is This Course For? Aspiring data scientists and AI enthusiasts who want to learn how to build deep learning models using TensorFlow. Software developers and engineers looking to enhance their machine learning and AI skills with hands-on TensorFlow projects. Students and professionals aiming to break into the AI field and develop practical skills for real-world applications. Researchers and analysts seeking to implement advanced neural networks and AI models for their work or projects. Beginners in machine learning who want a comprehensive introduction to TensorFlow and deep learning, no prior experience required. This course is perfect for anyone eager to master TensorFlow and apply it to build powerful AI models. Homepage https://www.udemy.com/course/tensorflow-for-deep-learning-build-ai-models-like-a-pro/ Rapidgator https://rg.to/file/fc1d1298c2f671c13a957635819cd74a/nlare.TensorFlow.for.Deep.Learning.Build.AI.Models.Like.a.Pro.part1.rar.html https://rg.to/file/58987379992cac3e67d66e1d873d0176/nlare.TensorFlow.for.Deep.Learning.Build.AI.Models.Like.a.Pro.part2.rar.html Fikper Free Download https://fikper.com/7Zf3StqxMS/nlare.TensorFlow.for.Deep.Learning.Build.AI.Models.Like.a.Pro.part1.rar.html https://fikper.com/NHPGxZUEXr/nlare.TensorFlow.for.Deep.Learning.Build.AI.Models.Like.a.Pro.part2.rar.html No Password - Links are Interchangeable

Free Download Generative Ai In Healthcare - Practical & Hands-On Learning Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.40 GB | Duration: 2h 44m Revolutionize Healthcare with Generative AI: Practical Projects and Real-world Applications What you'll learn Understand the fundamentals of Generative AI and its applications in healthcare. Implement hands-on projects to create AI models tailored for medical imaging and diagnostics. Analyze real-world healthcare datasets to generate AI-driven insights and solutions. Apply ethical considerations and best practices when using AI technologies in healthcare environments. Requirements Basic understanding of Artificial Intelligence and Machine Learning concepts (helpful but not required). Familiarity with Python programming for hands-on projects. Access to a computer with an internet connection to run AI tools and software. No prior healthcare experience needed-all necessary concepts will be explained during the course. Description Unlock the transformative potential of Generative AI in the healthcare industry with this comprehensive, hands-on course. Designed for healthcare professionals, AI enthusiasts, data scientists, and tech experts, this course provides a deep dive into the rapidly growing intersection of AI and healthcare. You'll gain both a strong theoretical foundation and practical skills to apply Generative AI models to real-world healthcare challenges.Throughout the course, you will explore various applications of Generative AI in healthcare, from personalized treatment recommendations to medical imaging analysis. You'll work on hands-on projects, implement cutting-edge AI models like Variational Autoencoders (VAE) and Generative Adversarial Networks (GAN), and understand how these models can be used to synthesize medical data.You'll also learn about critical topics like data privacy, ethical considerations, and regulatory compliance in deploying AI models in healthcare environments. By the end of the course, you'll be well-prepared to build, implement, and deploy Generative AI solutions that can significantly impact patient care and medical research.What You Will Learn:Overview and applications of Generative AI in healthcare.Implementation of advanced deep generative models such as VAEs and GANs.Personalized treatment recommendation, disease prediction, and medical imaging analysis using Generative AI.Ethical considerations and privacy-preserving techniques in healthcare AI.Advanced topics like transfer learning, adversarial attacks, and interpretability in AI models.Practical skills to deploy Generative AI models in healthcare, including on cloud platforms.Course Highlights:Hands-on Learning: Real-world projects and demos throughout the course, including AI model implementations and medical image analysis.Case Studies & Research: Explore relevant case studies, research papers, and the latest advancements in the use of Generative AI in healthcare.Ethics & Compliance: Understand the critical ethical and privacy concerns when handling healthcare data with AI technologies.Deployment Ready: Learn how to successfully deploy and monitor AI models in healthcare settings, meeting regulatory requirements.Whether you're looking to enhance patient care, work with medical data, or stay at the forefront of AI innovation in healthcare, this course will provide you with the essential tools and knowledge to succeed. Overview Section 1: Introduction to Generative AI in Health Care Lecture 1 Overview of generative AI Lecture 2 Applications of generative AI in health care Lecture 3 Challenges and opportunities Lecture 4 Hands-on: Setting up environment Lecture 5 Demo: Setting up environment Section 2: Understanding Deep Generative Models Lecture 6 Introduction to deep generative models Lecture 7 Types of deep generative models Lecture 8 Comparison of different models Lecture 9 Hands-on: Implementing a variational autoencoder Lecture 10 Demo: Implementing a variational autoencoder Lecture 11 Hands-on: Implementing a generative adversarial network Lecture 12 Demo: Implementing a generative adversarial network Section 3: Applications of Generative AI in Health care Lecture 13 Personalized treatment recommendation Lecture 14 Disease prediction and prevention Lecture 15 Medical imaging analysis Lecture 16 Hands-on: Building a Simple Medical Imaging Analysis Model Section 4: Generative AI for Medical Image Analysis Lecture 17 Importance of medical image analysis in health care Lecture 18 Generative models for medical image synthesis Lecture 19 Hands-on: Generating medical images using GANs Lecture 20 Demo: Generating medical images using GANs Section 5: Patient Data Privacy and Ethical Considerations Lecture 21 Privacy concerns in health care data Lecture 22 Ethical considerations in generative AI Lecture 23 Regulations and compliance Lecture 24 Hands-on: Implementing privacy-preserving techniques Lecture 25 Demo: Implementing privacy-preserving techniques Section 6: Ethical considerations in using Generative AI in Health care Lecture 26 Data privacy and security concerns Lecture 27 Bias and fairness in AI algorithms Lecture 28 Regulatory challenges Section 7: Advanced Topics in Generative AI for Health Care Lecture 29 Transfer learning in generative models Lecture 30 Adversarial attacks and defenses Lecture 31 Interpretability and explainability Lecture 32 Hands-on: Transfer learning for medical data Section 8: Deploying Generative AI Models in Health Care Lecture 33 Challenges of deploying AI models in health care Lecture 34 Regulatory requirements for deployment Lecture 35 Monitoring and updating models Lecture 36 Hands-on: Deploying a generative model on cloud platform Tech professionals seeking to explore AI-driven solutions in the medical field.,Data scientists and AI enthusiasts looking to specialize in healthcare applications of Generative AI.,Students and researchers curious about the intersection of AI and healthcare and eager to gain hands-on experience with real-world projects.,Healthcare professionals interested in leveraging AI to improve patient care and diagnostics. 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Free Download Federated Learning and Privacy-preserving RAGs Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 48 KHz Language: English | Size: 31.15 MB | Duration: 16m 1s Learn federated learning and privacy-preserving techniques. This course will teach you how to architect AI solutions while ensuring data privacy in Retrieval-Augmented Generation (RAG) systems. More and more organizations would like to implement Retrieval-Augmented Generation (RAG) solutions to enhance their customer experience integrating privacy-preserving techniques ensuring data security and regulatory compliance. In this course, Federated Learning and Privacy-preserving RAGs, you'll learn to design and implement advanced AI systems that prioritize data privacy without sacrificing performance. First, you'll explore the fundamentals of federated learning, including its principles and how it enables decentralized data processing. Next, you'll discover how to integrate privacy-preserving techniques into RAG models, such as homomorphic encryption and differential privacy, to safeguard sensitive information. Finally, you'll learn to implement these concepts practically, developing and deploying RAG systems that adhere to privacy regulations and protect user data. When you're finished with this course, you'll have the skills and knowledge needed to create robust, privacy-conscious RAG solutions that enhance AI performance while maintaining strict data protection standards. Homepage https://www.pluralsight.com/courses/federated-learning-privacy-preserving-rags TakeFile https://takefile.link/p81zpar7u6q9/hdtvz.Federated.Learning.and.Privacypreserving.RAGs.rar.html Rapidgator https://rg.to/file/9b0d210828f6091f9bee4737475d1de2/hdtvz.Federated.Learning.and.Privacypreserving.RAGs.rar.html Fikper Free Download https://fikper.com/XcE17yy6Gr/hdtvz.Federated.Learning.and.Privacypreserving.RAGs.rar.html No Password - Links are Interchangeable

Free Download Deep Learning for Natural Language Processing, Video Edition Released 10/2022 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 5h 48m | Size: 838 MB Explore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning! Inside Deep Learning for Natural Language Processing you'll find a wealth of NLP insights, including An overview of NLP and deep learning One-hot text representations Word embeddings Models for textual similarity Sequential NLP Semantic role labeling Deep memory-based NLP Linguistic structure Hyperparameters for deep NLP Deep learning has advanced natural language processing to exciting new levels and powerful new applications! For the first time, computer systems can achieve "human" levels of summarizing, making connections, and other tasks that require comprehension and context. Deep Learning for Natural Language Processing reveals the groundbreaking techniques that make these innovations possible. Stephan Raaijmakers distills his extensive knowledge into useful best practices, real-world applications, and the inner workings of top NLP algorithms. About the Technology Deep learning has transformed the field of natural language processing. Neural networks recognize not just words and phrases, but also patterns. Models infer meaning from context, and determine emotional tone. Powerful deep learning-based NLP models open up a goldmine of potential uses. About the Book Deep Learning for Natural Language Processing teaches you how to create advanced NLP applications using Python and the Keras deep learning library. You'll learn to use state-of the-art tools and techniques including BERT and XLNET, multitask learning, and deep memory-based NLP. Fascinating examples give you hands-on experience with a variety of real world NLP applications. Plus, the detailed code discussions show you exactly how to adapt each example to your own uses! What's Inside Improve question answering with sequential NLP Boost performance with linguistic multitask learning Accurately interpret linguistic structure Master multiple word embedding techniques About the Reader For readers with intermediate Python skills and a general knowledge of NLP. No experience with deep learning is required. About the Author Stephan Raaijmakers is professor of Communicative AI at Leiden University and a senior scientist at The Netherlands Organization for Applied Scientific Research (TNO). Homepage ? Explore the most challenging issues of natural language processing, and learn how to solve them with cutting-edge deep learning! TakeFile https://takefile.link/np3uzk1yejmp/nkqih.Deep.Learning.for.Natural.Language.Processing.Video.Edition.rar.html Rapidgator https://rg.to/file/239c455aecf3e5ad6e670e41dffa2f6f/nkqih.Deep.Learning.for.Natural.Language.Processing.Video.Edition.rar.html Fikper Free Download https://fikper.com/T55RNPIWWu/nkqih.Deep.Learning.for.Natural.Language.Processing.Video.Edition.rar.html No Password - Links are Interchangeable

Free Download Udemy - Curiosity And Lifelong Learning (2024) Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 5.35 GB | Duration: 5h 6m Unlock Innovation and Success: Explore Curiosity's Role in Memory, Problem-Solving, Lifelong Learning, and Cross-Cultura What you'll learn Explain the role of the brain's reward systems in stimulating curiosity and lifelong learning. Illustrate how curiosity activates memory formation and enhances long-term knowledge retention. Apply creative problem-solving techniques influenced by neuroscientific studies on curiosity. Analyze cases of individuals whose curiosity led to groundbreaking work in their fields. Discuss the psychological drivers that fuel the process of curiosity in learning. Evaluate the impact of curiosity on cognitive flexibility, adaptability, and resilience. Create strategies for using curiosity to improve critical thinking and decision-making in complex situations. Relate the emotional benefits of curiosity to its impact on mental well-being through real-world examples. Develop a framework for fostering a curiosity-driven innovation culture in various industries. Formulate techniques to maintain curiosity in environments focused on creativity and discovery. Design a personal continuous learning plan emphasizing the cultivation of curiosity. Assess the relationship between a growth mindset and curiosity in lifelong learning journeys. Use digital tools effectively to enhance curiosity and engage with reliable information. Construct methods for encouraging open-minded exploration to enhance critical thinking and problem-solving. Implement a curiosity-driven culture in the workplace that fosters innovation and productivity. Synthesize knowledge from different domains to foster innovation and interdisciplinary thinking. Generate a personal development plan that utilizes curiosity to unlock new career and life opportunities. Facilitate curiosity in others through practical approaches in mentoring, teaching, and leadership. Overcome common barriers to curiosity, such as fear of failure and comfort zone complacency. Prepare a curiosity-based questioning strategy to gain deeper insights into complex problems. Requirements There are no requirements or pre-requisites for this course, but the items listed below are a guide to useful background knowledge which will increase the value and benefits of this course. A basic understanding of psychological concepts, particularly those related to learning and cognitive development. Familiarity with using digital tools and the internet for research and learning purposes. An open-minded approach to exploring new ideas and concepts across a variety of disciplines. Description Are you ready to embark on a transformative learning journey that will ignite your curiosity, enhance your problem-solving skills, and drive innovation in both your personal and professional life? Welcome to the comprehensive course on "The Power of Curiosity: Unleashing Lifelong Learning and Innovation"!In today's fast-paced world, cultivating a mindset of curiosity is more critical than ever. Research has shown that curiosity not only stimulates the brain's reward systems but also plays a vital role in driving lifelong learning and fostering creativity. By harnessing the power of curiosity, you can enhance your critical thinking, decision-making skills, and adaptability in navigating complex challenges.Throughout this course, we will delve deep into the psychology of curiosity, exploring how it influences cognitive flexibility, resilience, and emotional well-being. You will discover practical strategies to spark curiosity in yourself and others, paving the way for continuous growth and success in various aspects of life.From understanding how curiosity fuels innovation to developing a curiosity-driven mindset for personal and professional growth, each module will equip you with valuable insights and tools to unlock your full potential. By building a culture of curiosity in your workplace and embracing interdisciplinary thinking, you will be primed to drive groundbreaking ideas and collaborations.In the digital age, where information is abundant yet overwhelming, I will show you how to navigate the vast landscape with curiosity as your compass. By honing your critical thinking and problem-solving skills through curiosity-driven inquiry, you will be able to tackle challenges with curiosity and resilience.Through real-world examples, case studies, and practical exercises, you will not only enhance your skills but also develop a lifelong curiosity roadmap that will guide you towards continuous learning and personal growth. Whether you are a seasoned professional seeking career advancement or a lifelong learner hungry for new knowledge, this course is designed to cater to your needs and aspirations.Join me on this extraordinary journey of discovery, where curiosity is not just a trait but a powerful tool for transformation. Together, we will unleash the true potential of your curious mind and pave the way for a future filled with endless possibilities. Enroll now and let curiosity be your guide to lifelong learning and innovation. Let's embark on this enriching adventure together! Overview Section 1: The Science Behind Curiosity: Understanding Its Neuroscientific Foundations Lecture 1 How curiosity stimulates the brain and its role in driving lifelong learning Lecture 2 Download The *Amazing* +100 Page Workbook For this Course Lecture 3 Introduce Yourself To Your Fellow Students And Tell Us What You Want To Learn Lecture 4 Exploring the brain's reward systems activated by curiosity and exploration Lecture 5 The link between curiosity, memory formation, and long-term knowledge retention Lecture 6 Neuroscientific studies on how curiosity enhances creativity and problem-solving Lecture 7 Real-world examples of individuals who harnessed curiosity for groundbreaking wo Lecture 8 Let's Celebrate Your Progress In This Course: 25% > 50% > 75% > 100%!! Section 2: The Psychology of Curiosity: How It Shapes Our Learning and Thinking Lecture 9 Understanding the psychological drivers that fuel curiosity in learning processe Lecture 10 The role of curiosity in fostering cognitive flexibility, adaptability, and resi Lecture 11 How curiosity influences critical thinking and decision-making in complex situat Lecture 12 The emotional benefits of a curious mindset and its impact on mental well-being Lecture 13 Case studies of how curiosity enhanced problem-solving in various industries Section 3: How Curiosity Drives Innovation and Breakthrough Thinking Lecture 14 Why curiosity is a key factor in innovation and how it leads to groundbreaking i Lecture 15 Techniques to spark curiosity in environments focused on creativity and discover Lecture 16 How curiosity-driven exploration leads to cross-disciplinary insights and innova Lecture 17 Lessons from history: how curiosity led to major scientific and technological ad Lecture 18 Case studies of companies where curiosity-driven cultures led to innovations Section 4: Fostering a Lifelong Learning Mindset Through Curiosity Lecture 19 Understanding how curiosity fuels a commitment to continuous personal developmen Lecture 20 The relationship between curiosity and a growth mindset in lifelong learning jou Lecture 21 Strategies for cultivating a mindset of curiosity in learning new skills and kno Lecture 22 How curiosity leads to persistence, grit, and resilience in lifelong learning en Lecture 23 Real-world examples of lifelong learners who attribute success to curiosity Section 5: Practical Strategies for Harnessing Curiosity in the Digital Age Lecture 24 Navigating the vast information landscape with curiosity as a guide to learning Lecture 25 How to use digital tools to feed curiosity and find reliable, engaging informati Lecture 26 Building digital literacy through curiosity: questioning, exploring, and discove Lecture 27 How to filter and prioritize information in the digital age for lifelong learnin Lecture 28 Real-life examples of individuals leveraging the internet to deepen curiosity Lecture 29 You've Achieved 25% >> Let's Celebrate Your Progress And Keep Going To 50% >> Section 6: The Role of Curiosity in Developing Critical Thinking and Problem-Solving Lecture 30 How curiosity enhances critical thinking by encouraging open-minded exploration Lecture 31 Practical ways to use curiosity to approach complex, ambiguous problems Lecture 32 The link between curiosity and developing new perspectives on old challenges Lecture 33 How to build problem-solving strategies by fostering curiosity in work and life Lecture 34 Case studies of critical problems solved by teams and individuals with curious m Section 7: Building a Culture of Curiosity in the Workplace for Innovation Lecture 35 How to create a workplace environment that encourages curiosity and exploration Lecture 36 The importance of leadership in fostering curiosity-driven innovation in teams Lecture 37 Tactics to integrate curiosity as part of daily routines and workflows in the of Lecture 38 How to measure the impact of curiosity-driven culture on workplace productivity Lecture 39 Real-world case studies of companies that built cultures of curiosity and thrive Section 8: How Curiosity Enhances Interdisciplinary Thinking and Learning Lecture 40 Why curiosity fosters interdisciplinary collaboration and leads to breakthrough Lecture 41 Techniques for applying curiosity across different domains to discover new insig Lecture 42 The value of exploring diverse fields to cultivate curiosity-driven knowledge ex Lecture 43 Curiosity-driven learning: blending science, art, business, and technology for g Lecture 44 Examples of cross-disciplinary thinkers who embraced curiosity for innovation Section 9: Developing Curiosity as a Key Skill for Personal Growth and Success Lecture 45 The connection between curiosity, personal development, and lifelong success Lecture 46 How to cultivate curiosity to unlock new opportunities in career and personal li Lecture 47 The role of curiosity in expanding emotional intelligence and interpersonal skil Lecture 48 Creating a personal curiosity framework for continuous growth and learning Lecture 49 Real-life stories of individuals who developed personal success through curiosit Section 10: Encouraging Curiosity in Others: Mentoring, Teaching, and Leading Lecture 50 The importance of mentoring and teaching to cultivate curiosity in others Lecture 51 How to create a learning environment that nurtures curiosity in students or ment Lecture 52 Practical approaches to inspire curiosity in teams, colleagues, and direct repor Lecture 53 How to lead by example: demonstrating curiosity as a leadership trait Lecture 54 Examples of leaders and mentors who sparked curiosity in others for lasting impa Lecture 55 You've Achieved 50% >> Let's Celebrate Your Progress And Keep Going To 75% >> Section 11: Cultivating Curiosity for Professional Development and Career Growth Lecture 56 How curiosity fuels career growth by encouraging exploration and adaptability Lecture 57 Practical ways to use curiosity to seek out new roles, skills, and career paths Lecture 58 Curiosity-driven networking: how to ask better questions and make lasting connec Lecture 59 Turning curiosity into a competitive advantage in career advancement and learnin Lecture 60 Case studies of professionals who leveraged curiosity for career success Section 12: Overcoming Curiosity Inhibitors: Fear, Failure, and Comfort Zones Lecture 61 Understanding the common barriers that suppress curiosity in individuals and tea Lecture 62 How fear of failure, criticism, and the unknown can dampen curiosity in learning Lecture 63 Practical strategies to overcome internal and external inhibitors of curiosity Lecture 64 How to push beyond comfort zones by cultivating curiosity in new experiences Lecture 65 Real-life examples of individuals who overcame curiosity blocks for growth Section 13: Curiosity in Problem-Solving: Asking Better Questions for Deeper Insights Lecture 66 How curiosity leads to asking more insightful questions that drive effective sol Lecture 67 Techniques for improving questioning skills to spark curiosity in problem-solvin Lecture 68 How to guide teams and individuals to develop curiosity-driven questioning strat Lecture 69 Case studies of complex problems solved through curiosity-led inquiry and resear Lecture 70 Examples of curiosity-driven question frameworks used in innovation processes Section 14: The Role of Curiosity in Building Resilience and Adaptability Lecture 71 How curiosity builds emotional and cognitive resilience in uncertain times Lecture 72 The role of curiosity in staying adaptable and flexible in rapidly changing envi Lecture 73 Curiosity-driven exploration as a key element of personal and professional resil Lecture 74 Practical techniques to foster curiosity in times of failure and adversity Lecture 75 Case studies of individuals who used curiosity to overcome challenges and thrive Section 15: Curiosity and the Power of Exploration in Learning New Skills Lecture 76 How exploration fuels the acquisition of new skills and continuous improvement Lecture 77 Practical steps to follow curiosity into learning new skills across diverse area Lecture 78 Techniques for developing a curiosity-based skill acquisition strategy for succe Lecture 79 How curiosity leads to learning opportunities in unexpected and unplanned areas Lecture 80 Examples of how curiosity sparked lifelong learning journeys for individuals Lecture 81 You've Achieved 75% >> Let's Celebrate Your Progress And Keep Going To 100% >> Section 16: Curiosity in Communication: Enhancing Listening, Observation, and Inquiry Lecture 82 How curiosity improves communication by encouraging deeper listening and underst Lecture 83 Techniques to use curiosity to ask meaningful questions in conversations and mee Lecture 84 The role of curiosity in improving observation skills and noticing hidden detail Lecture 85 Building better communication and empathy through curiosity-driven dialogue Lecture 86 Case studies of how curiosity improved workplace communication and relationships Section 17: How Curiosity Supports Cross-Cultural Understanding and Collaboration Lecture 87 The role of curiosity in exploring different cultures, perspectives, and experie Lecture 88 How curiosity leads to greater cultural empathy, tolerance, and collaboration Lecture 89 Practical strategies for fostering curiosity in global teams and cross-cultural Lecture 90 Curiosity-driven learning: expanding horizons by exploring diverse cultural prac Lecture 91 Real-world examples of curiosity-driven cross-cultural success in business and s Section 18: Lifelong Curiosity: Developing Habits That Sustain Curiosity Over Time Lecture 92 How to build and sustain curiosity as a long-term habit in personal and professi Lecture 93 Practical methods for incorporating curiosity-driven learning into daily routine Lecture 94 Curiosity as a driver for staying mentally active, engaged, and open-minded in l Lecture 95 Creating lifelong learning goals fueled by curiosity in various areas of interes Lecture 96 Real-world examples of lifelong learners who used curiosity as a lifelong motiva Section 19: The Intersection of Curiosity, Mindfulness, and Self-Reflection Lecture 97 How curiosity plays a role in mindfulness practices and self-reflective thinking Lecture 98 Techniques for combining curiosity and mindfulness to deepen learning experience Lecture 99 Using curiosity to gain new insights in personal growth and self-awareness Lecture 100 Practical exercises for cultivating curiosity-driven reflection and mindful expl Lecture 101 Real-life examples of individuals using curiosity to enhance mindfulness and sel Section 20: Putting It All Together: Creating Your Personal Curiosity Roadmap Lecture 102 How to create a personal plan for harnessing curiosity in lifelong learning jour Lecture 103 Best practices for integrating curiosity into professional development and perso Lecture 104 Setting curiosity-driven goals for continuous exploration and development in lif Lecture 105 Building a curiosity-centered network of resources, mentors, and learning experi Lecture 106 Final project: developing a curiosity roadmap for personal and professional succ Lecture 107 You've Achieved 100% >> Let's Celebrate! Remember To Share Your Certificate!! Section 21: Your Assignment: Write down goals to improve your life and achieve your goals!! Early-career professionals looking to accelerate their career growth through enhanced creativity and problem-solving skills.,Lifelong learners interested in self-improvement, continuous personal development, and acquiring new knowledge and skills across various domains.,Educators and trainers seeking innovative ways to spark curiosity in their students or trainees to foster a more engaging and effective learning environment.,Corporate leaders and managers aiming to build a culture of innovation and adaptability within their teams by encouraging curiosity and open-minded exploration of new ideas and challenges.,Entrepreneurs and startup founders looking for inspiration and techniques to lead their ventures through curiosity-driven innovation and cross-disciplinary insights.,Mid-career professionals facing stagnation and looking to reinvent their career paths by embracing a curiosity-fueled approach to professional development and networking. 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Free Download Udemy - Continual Learning Published 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 3h 30m | Size: 1.23 GB Learn Continual Learning Techniques from Scratch Using PyTorch What you'll learn Understand Deep Learning and Neural Networks: Start with core concepts, laying the foundation for advanced deep learning techniques. Implement Neural Networks Without Libraries: Build neural networks from scratch, deepening your understanding of their core mechanics. Build Neural Networks with PyTorch: Master the construction of neural networks using PyTorch, a leading deep learning framework. Learn Continual Learning Techniques: Explore UER, SER, LwF, and EWC, and understand their application in adaptive AI systems. Implement Continual Learning in PyTorch: Apply continual learning algorithms from scratch using PyTorch, preparing for real-world AI challenges. Leverage deep learning in resource-constrained environments. Requirements Python Programming Language Description Unlock the potential of continual learning-a cutting-edge approach that allows machine learning models to adapt and learn from new data over time without forgetting previous knowledge. In this comprehensive course, you will gain both a strong theoretical foundation and hands-on experience in implementing continual learning techniques using PyTorch, one of the most widely used deep learning frameworks.This course begins by introducing the core concepts of deep learning and neural networks, ensuring a solid understanding of how models learn and evolve. From there, you will dive into key continual learning strategies such as Experience Replay (ER), Knowledge Distillation (KD), and Elastic Weight Consolidation (EWC). Each technique will be explored in detail, along with practical coding sessions where you'll build these methods from scratch using PyTorch.By the end of the course, you will:Master the fundamentals of deep learning and explore its application in continual learning.Implement continual learning techniques from scratch, including experience replay, Elastic Weight Consolidation (EWC), and knowledge distillation.Understand regularization and normalization methods to prevent overfitting and manage shifting data patterns over time.Build and train custom neural networks that can incrementally learn new tasks without forgetting previous ones.Apply continual learning algorithms to both regression and classification problems, preparing you for real-world applications.Leverage deep learning in resource-constrained environments.This course is designed for machine learning enthusiasts, developers, and researchers who want to take their deep learning skills to the next level and become proficient in continual learning. Whether you're familiar with PyTorch or new to it, this course will guide you through every step, making it accessible and rewarding for learners at various levels. Who this course is for Continual Learning Enthusiasts Homepage https://www.udemy.com/course/continual-learning/ Rapidgator https://rg.to/file/397d53bc4c4c0d7201d88ba9a18a1e61/gllzn.Continual.Learning.part1.rar.html https://rg.to/file/7783f4423180acb23453fa1864cfe87b/gllzn.Continual.Learning.part2.rar.html Fikper Free Download https://fikper.com/a3WVGNrwLr/gllzn.Continual.Learning.part1.rar.html https://fikper.com/hho1VdkbB3/gllzn.Continual.Learning.part2.rar.html No Password - Links are Interchangeable

Free Download Stepwise Guide to Learning Guitar in Sheet Music Published 9/2024 Created by Bob Saha MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 26 Lectures ( 1h 7m ) | Size: 1.24 GB Complete beginners and intermediate course for learning guitar in sheet music What you'll learn: Learning Guitar from Scratch clubbed with theory, practical and sheet music A comprehensive basic guitar tutorial with step-wise guide to learning Guitar from basic Learning to Strum and Sing, read the sheet music and tablatures Building strong foundation on Guitar basics including Staff notations and aural developments Suitable for basic and intermediate learners. Requirements: No prior learning experience or knowledge needed to start learning guitar. You should have a working guitar with you You will learn whatever you need to know Description: Stepwise Guide to Learning Guitar in Sheet Music may sound ambitious, but with focused effort and the right approach, you can make significant progress in a short amount of time. Start by familiarizing yourself with the anatomy of the guitar, including the different parts and their functions. Understanding essential terminology, like strings, frets, and picks, establishes a solid foundation. Devote the first few hours to mastering basic chords such as G, C, D, and A, as these form the backbone of countless songs. Practice transitioning between these chords to build your muscle memory and dexterity, crucial elements for smooth playing.To begin, it's essential to familiarize yourself with the basics of musical notation, including the staff, clefs, note values, and rests. For guitar players, the treble clef is primarily used, as it represents the range of the instrument effectively. Through consistent practice, musicians can improve their ability to quickly identify notes on the staff, enhancing their sight-reading skills-an invaluable asset in both solo and ensemble playing.As you progress, incorporating sheet music into your practice routine can help develop your ear and improve your overall musicianship. Start with simple melodies, gradually challenging yourself with more complex compositions as your confidence grows. Combine your sheet music practice with learning chords and techniques to understand how the written notes translate to the guitar fretboard. Utilizing a metronome while practicing can further enhance your timing and rhythm, crucial elements in delivering a polished performance.Overall, learning sheet music for guitar not only broadens your technical abilities but also nurtures creativity. With a solid foundation in reading music, guitarists can explore improvisation, composition, and collaboration with other musicians, ultimately enriching their journey in the world of music.As you gain confidence with basic chords, it's time to explore strumming patterns. Simple downstrokes and upstrokes create the rhythm that elevates your playing. Incorporating a metronome can help develop your timing and ensure that your strumming remains steady. In the following hours, delve into finger exercises to strengthen your fingers and improve your ability to navigate the fretboard. Scales, especially the pentatonic scale, are not only essential for solos but also enhance your overall musicality. By practicing these scales, you'll lay the groundwork for improvisation and creativity in your playing.Once you've covered the basics, tackle some intermediate techniques such as barre chords, which will greatly expand your chord repertoire. Additionally, learning about different musical styles and genres can inspire you to diversify your playing. Consider setting aside time to learn a few simple songs that you love; this will keep the practice engaging and reinforce your skills in a joyful way. Remember, while 24 hours is a great kickstart, consistent practice and patience are key to truly mastering the guitar over time. With dedication and a structured approach, you'll be well on your way to becoming a skilled guitarist. Who this course is for: This course is for absolute beginners as well as the intermediate learners Homepage https://www.udemy.com/course/learn-guitar-in-24-hours-r/ Rapidgator https://rg.to/file/d6d0a370730bc5b106495f95348a098d/rrife.Stepwise.Guide.to.Learning.Guitar.in.Sheet.Music.part1.rar.html https://rg.to/file/867c0ca1de147297b509d643a8aad1a9/rrife.Stepwise.Guide.to.Learning.Guitar.in.Sheet.Music.part2.rar.html Fikper Free Download https://fikper.com/RknJiEczW5/rrife.Stepwise.Guide.to.Learning.Guitar.in.Sheet.Music.part1.rar.html https://fikper.com/oz8sBlhbvp/rrife.Stepwise.Guide.to.Learning.Guitar.in.Sheet.Music.part2.rar.html No Password - Links are Interchangeable

Free Download Master Program In Machine Learning & Artificial Intelligence Published 9/2024 Created by IIBM Institute of Business Management MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 20 Lectures ( 28h 13m ) | Size: 16.2 GB Advanced study in ML/AI: algorithms, deep learning, NLP, ethics, big data, hands-on projects, and research opportunities What you'll learn: Foundations of AI & ML Machine Learning Algorithms Data Analytics Business Analysis Data Science with R SQL Database Data Science with Python Deep Learning Natural Language Processing Data Visualization Using Tableau Big Data Requirements: Fresh Graduates/ Diploma in any discipline or equivalent with minimum 1 Year of working Professionals Description: The Master's program in Machine Learning and Artificial Intelligence offers an extensive curriculum designed to provide students with both theoretical knowledge and practical skills in these rapidly evolving fields. The program begins with foundational coursework in mathematics and programming, covering essential topics such as linear algebra, calculus, probability, and advanced programming techniques. Core courses delve into machine learning algorithms, including supervised and unsupervised learning methods, neural networks, and deep learning techniques.Students explore natural language processing (NLP) to understand and develop systems for text and speech analysis, and computer vision for interpreting visual data. The program also addresses the ethical implications of AI, focusing on issues like fairness, bias, and societal impact.Hands-on experience is a key component, with opportunities for practical projects, internships, and a research thesis or capstone project that allows students to apply their knowledge to real-world challenges. With a focus on both theoretical understanding and practical application, graduates are prepared for careers in data science, AI research, and machine learning engineering. The program typically spans 1 to 2 years and offers online study options, with some programs available online from IIBM Institute.Advanced study in ML/AI: algorithms, deep learning, NLP, ethics, big data, hands-on projects, and research opportunities. 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