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Free Download Pluralsight - Automating Azure DevTest Labs Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 48 KHz Language: English | Size: 80.95 MB | Duration: 26m 37s Learn how to automate Azure DevTest Labs efficiently. This course will teach you how to streamline resource management, deploy environments, manage artifacts, and integrate automation into CI/CD pipelines for optimized workflows. Many organizations struggle with the manual management of development and test environments, leading to inefficiencies and increased costs. In this course, Automating Azure DevTest Labs, you'll learn to streamline resource management and automate tasks within Azure DevTest Labs. First, you'll explore how to configure automation for managing lab environments, including VM lifecycle and resource optimization. Next, you'll discover how to apply and manage artifacts of Azure DevTest Labs environments. Finally, you'll learn how to integrate DevTest Labs automation into CI/CD pipelines for seamless provisioning. When you're finished with this course, you'll have the skills and knowledge to automate Azure DevTest Labs, reducing manual effort, enhancing consistency, and optimizing costs. Homepage https://www.pluralsight.com/courses/azure-devtest-labs-automating Screenshot Rapidgator https://rg.to/file/fe5f1f1cc523cd132fcc8807d7c2ad1b/rwyog.Automating.Azure.DevTest.Labs.rar.html Fikper Free Download https://fikper.com/pg4VkN8UhP/rwyog.Automating.Azure.DevTest.Labs.rar.html No Password - Links are Interchangeable

Free Download Automating Ml Pipelines For Song Recommendation System Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.74 GB | Duration: 4h 46m Automate Song Recommendations with Docker, MLFlow, and CI/CD Practices for Machine Learning Algorithms. What you'll learn Understand the Math Behind ML Algorithms: You will learn the mathematical concepts that underlie popular machine learning algorithms. Implement Machine Learning Algorithms: You will gain hands-on experience in coding and applying various machine learning algorithms. Design and Build MLFlow Tracking: You will learn how to use MLFlow for tracking and managing machine learning experiments effectively. Implement Microservices with Docker: You will learn how to create and manage microservices for automating machine learning pipelines using Docker. Automate Model Training and Evaluation: You will learn to use Airflow triggers to automate the process of training and evaluating machine learning models. Set Up Git CI/CD for a Song Recommender App: You will learn how to implement CI/CD for a song recommendation web app. Requirements Basic Knowledge of Python programming, as it will be used for implementing machine learning algorithms and building ML pipeline microservices. A desire to learn and experiment with machine learning and microservices is encouraged. Description Math Behind Machine Learning Algorithms:K-Nearest Neighbors (KNN): A method for finding similar songs based on user preferences.Random Forest (RF): An algorithm that combines many decision trees for better predictions.Prin[beeep]l Component Analysis (PCA): A technique for reducing the number of features while retaining important information.K-Means Clustering: A way to group similar songs together based on features.Collaborative Filtering: Making recommendations based on user interactions and preferences.Data Processing Techniques:Feature Engineering (Feature Importance using Random Forest): Feature importance analysis and creating new features from existing data to improve model accuracy.Data Pre-processing (Missing Data Imputation): Cleaning and preparing data for analysis.Evaluation and Tuning:Hyperparameter Tuning (Collaborative Filtering, KNN, Naive Bayes Classifier): Adjusting the settings of algorithms to improve performance.Evaluation Metrics (Precision, Recall, ROC, Accuracy, MSE): Methods to measure how well the model performs.Data Science Fundamentals:TF-IDF (Term Frequency and Inverse Document Frequency): A technique for analyzing the importance of words in song lyrics.Correlation Analysis: Understanding how different features relate to each other.T-Test: A statistical method for comparing groups of data.Automation Tools:Building Microservices using Docker: Use containers to run applications consistently across different environments.Airflow: Automate workflows and schedule tasks for running ML models.MLFlow: Manage and track machine learning experiments and models effectively.By the end of the course, you will know how to build and automate the training, evaluation, and deployment of an ML model for a song recommendation system using these tools, libraries and techniques. Overview Section 1: Introduction Lecture 1 Course Introduction Section 2: Machine Learning - Math Intuition Lecture 2 Math Behind Collaborative Filtering Lecture 3 Math Behind KNN (Euclidean Distance) Lecture 4 Math Behind Naive Bayes (Bayes Theorem) Lecture 5 Math Behind TF and IDF Lecture 6 Math Behind Cosine Similarity Lecture 7 Evaluation Metric - MSE Lecture 8 Math Behind - K-Means Clustering (Unsupervised Learning) Lecture 9 Math Behind Prin[beeep]l Component Analysis Lecture 10 Math Behind Pearson Correlation Lecture 11 Math Behind - T-Statistic Test Lecture 12 Evaluation Metrics - Classification Models Section 3: ML Experimentation - Supervised & Unsupervised Learning Lecture 13 Module Artifacts Lecture 14 Project Env Setup (Conda) Lecture 15 Import required libraries Lecture 16 Understanding the features in data Lecture 17 Data Preprocessing Lecture 18 Feature Engineering Lecture 19 Pearson Correlation Analysis Lecture 20 T-Test Statistics Lecture 21 Collaborative Filtering - User Genre Matrix Lecture 22 Creation of user similarity network visualization (Cosine Similarity) Lecture 23 Songs Recommender Engine Model - Collaborative Filtering Lecture 24 Fetch Songs Recommendation - Collaborative Filtering Model Lecture 25 KNN and Naive Bayes Model Pipeline Lecture 26 Model Hyperparameter Tuning Lecture 27 Best Estimator Recommendation Lecture 28 K-Means Clustering and PCA Section 4: Airflow - Automate Collaborative Filtering model training and deployment Lecture 29 Module Artifacts Lecture 30 Code Environment Setup Lecture 31 MLFlow Lifecycle and Commands Lecture 32 Airflow Lifecycle and Commands Lecture 33 DAG Setup - Data Splitting, User Genre Matrix Generation, Training & Evaluation Lecture 34 train_and_deploy.py W/O Airflow Lecture 35 Optional - DAG Assets Validation Section 5: Building Microservices for MLFlow and Airflow using Docker Lecture 36 docker-compose.yml Lifecycle (Theory) Lecture 37 Dockerfile (Python and Airflow) Lecture 38 Microservices - docker-compose.yml Lecture 39 Building Docker Image for Python Lecture 40 Building Docker Image for Airflow Section 6: ML Pipeline Orchestration - Airflow Triggers and MLFlow Experiments Lecture 41 Build and Compose up the Microservices Lecture 42 Orchestrating the ML Job Triggers and Logs Section 7: Song Recommender System Web App Lecture 43 Import required modules Lecture 44 Load Pkl Model Lecture 45 Fallback condition for recommender system Lecture 46 Load and Fetch cache Data Lecture 47 Building UI for song recommender system Lecture 48 Filter and Join recommendations Lecture 49 Testing the recommender app in localhost environment Lecture 50 Push the codebase to Github repository Lecture 51 Deploy recommender app to Streamlit cloud with Github CI/CD Section 8: Challenges / Takeaways / Homework Lecture 52 Automating ML Pipeline Song Recommendation: Challenges / Takeaways / Homework Lecture 53 Thank you! Lecture 54 Codebase Artifacts Students pursuing studies in data science, computer science, or related disciplines who want to enhance their practical skills in machine learning and automation.,Individuals looking to deepen their understanding of machine learning and its applications in real-world scenarios, particularly in recommendation systems.,Programmers interested in expanding their skill set to include machine learning concepts and automation practices using tools like Docker, MLFlow, and Airflow.,Professionals wanting to learn how to build and automate machine learning pipelines and improve their workflow efficiency.,Anyone with a foundational knowledge of machine learning who wants to gain practical experience in implementing algorithms and automating processes.,Individuals looking to enhance their qualifications and job prospects by adding machine learning and automation expertise to their portfolio. 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Free Download Automating BGP Routing Security with gRPC, gNMI, and YDK Duration: 1h 41m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 48 kHz, 2ch | Size: 356 MB Genre: eLearning | Language: English This course demonstrates how a combination of modern software technologies, such as IP routing, network security, and device automation, can be used to thwart denial of service attacks. IP routing, network security, and device automation can powerfully combine to solve real-life business problems. In this course, Automating BGP Routing Security with gRPC, gNMI, and YDK, you'll first gain insight regarding the business scenario that the remainder of the course will address. This includes a detailed network review, plus some preparatory automation work. Next, you'll develop Python scripts using Google Remote Procedure Call (gRPC) and gRPC Network Management Interface (gNMI) to automate the injection of routes onto a network device. This course teaches you the core gRPC and gNMI technologies without using pre-made simplification libraries. Last, you'll see how to solve the business problem a different way, using the YANG Development Kit (YDK). This powerful tool introduces additional structure to your software design. When you're finished with this course, you'll have the skills necessary to automate network devices using gRPC, gNMI, and YDK. While the use-cases may differ over time, the method by which these tools are deployed remains the same. Homepage https://pluralsight.com/courses/bgp-routing-security-grpc-gnmi-ydk-automating-cert/ Rapidgator https://rg.to/file/a847a565949613aad6dfebc0de31deeb/pavkx.Automating.BGP.Routing.Security.with.gRPC.gNMI.and.YDK.rar.html Fikper Free Download https://fikper.com/1oBBbh42zW/pavkx.Automating.BGP.Routing.Security.with.gRPC.gNMI.and.YDK.rar.html 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 AIOps Foundations - Automating IT Operations using AI Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Beginner | Genre: eLearning | Language: English + srt | Duration: 1h 22m | Size: 197 MB Amid the ever-evolving IT landscape, organizations strive for operational efficiency and peak performance. However, managing intricate IT ecosystems can present challenges in maintaining uptime, resolving issues promptly, and optimizing processes. Enter AIOps, a game-changing solution poised to reshape IT management practices and set new benchmarks. In this course, management consultant Priya Mohan guides you through a comprehensive exploration of AIOps, covering topics such as data collection, anomaly detection, predictive maintenance, and strategic implementation. Dive into the transformative advantages of implementing AIOps, including substantial savings as you curb downtime, enhance resource allocation, empower your teams to shift from reactive firefighting to strategic planning, and enable accurate forecasting. By the end of the course, you will confidently deploy AI-powered solutions to optimize IT operations, reduce downtime, and enhance overall performance. Homepage https://www.linkedin.com/learning/aiops-foundations-automating-it-operations-using-ai/ TakeFile https://takefile.link/1nlg8t1pwn9h/sfvke.AIOps.Foundations.Automating.IT.Operations.using.AI.rar.html Rapidgator https://rg.to/file/05409d25fafd30841e31c57e08e4ec8a/sfvke.AIOps.Foundations.Automating.IT.Operations.using.AI.rar.html Fikper Free Download https://fikper.com/Vx6QhjCzD8/sfvke.AIOps.Foundations.Automating.IT.Operations.using.AI.rar.html No Password - Links are Interchangeable

epub | 22.91 MB | English | Isbn:9781837631421 | Author: Dennis Chow, David Bruskin (Foreword by) | Year: 2024 About ebook: Automating Security Detection Engineering: A hands-on guide to implementing Detection as Code https://rapidgator.net/file/fec52b5aed6f6c3211e138d9aa33b9ab/ https://nitroflare.com/view/A4659077855337D/

Maintaining, Troubleshooting, Automating in ArcGIS Server MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 280 MB Genre: eLearning | Language: English ArcGIS Server provides a backbone for web maps and applications. Users can publish data from shapefiles, files, and enterprise geodatabases to allow for customized display and access in web maps and applications. ArcGIS provides a scalable framework for implementing GIS solutions for a single user or many users on desktops, in servers, over the web, and in the field.This course will instruct viewers how to deploy ArcGIS Server, publish and consume services via ArcGIS and third-party platforms. It starts with optimizing and monitoring the services. After that, you'll learn how to configure a secure environment and control who has access to your services. In the third section, you'll understand how to automate common server administration and data management tasks using the ArcGIS REST API, ArcPy and command line utilities. in the last section of this course, address some common issues that arise with installing and administering your server and publishing your services. This series instructs viewers how to maintain, troubleshoot, and fine-tune your ArcGIS Server and services and automate server management tasks. Download From NitroFlare http://nitroflare.com/view/2A296ADBC43BB0D/xidau123_MaintainingTroubleshootingAutomatinginArcGIS.rar Download From UploadGig https://uploadgig.com/file/download/C2c8eA30cCeB5718/xidau123_MaintainingTroubleshootingAutomatinginArcGIS.rar Download From Rapidgator https://rapidgator.net/file/aa174ec242e1fac90dee23bd6574af28/xidau123_MaintainingTroubleshootingAutomatinginArcGIS.rar.html

Automating AWS and vSphere with Terraform MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1.5 Hours | 218 MB Genre: eLearning | Language: English Learn how to use Terraform with AWS and vSphere. Starting with an overview of Terraform, you'll learn about where and how Terraform can be used, how to code in Terraform, and more. Terraform is an exciting tool that allows you to quickly automate and spin up entire environments easily. The tool continues to gain traction in the community, particular in the Public Cloud space as developers can not only deploy workloads, but update the state of the entire stack. This course, Automating AWS and vSphere with Terraform, will teach how you can use Terraform to create automated deployments of resources in AWS and vSphere. First, you will learn how to install Terraform, configure Terraform providers, as well as how to deploy specific resource constructs into each of those providers. Next, you will learn how to code in the Terraform language and look at Local and Remote Provisioners. By the end of this course, you will have a fundamental understanding of Terraform which you can build upon in the Public Cloud or Private Data Center. Download From UploadGig https://uploadgig.com/file/download/591241a91C4a1065/xidau123_PluralsightAutomatingAWSandvSpherewithTerr.rar Download From NitroFlare http://nitroflare.com/view/8D3091AD014DC63/xidau123_PluralsightAutomatingAWSandvSpherewithTerr.rar Download From Rapidgator http://rapidgator.net/file/f15c27d546cce60e713b616abf45447b/xidau123_PluralsightAutomatingAWSandvSpherewithTerr.rar.html

Automating AWS with CloudFormation .MP4, AVC, 226 kbps, 1280x720 | English, AAC, 96 kbps, 2 Ch | 1h 19m | 168 MB Instructor: Andreas Wittig Amazon's Cloud is 10 times bigger than its next 10 competitors combined. As an AWS customer, you benefit from a fast-growing and innovative platform. You probably started to manage your cloud infrastructure by clicking through the AWS Management Console. But managing growing AWS environments manually is complex and fault-prone. This course, Automating AWS with CloudFormation, will teach you the skills you need to automate your cloud infrastructure. First, you will learn how to describe your infrastructure in code, also called Infrastructure as Code. Next, you will dive into CloudFormation, which allows you to describe your infrastructure in a template, and finally, you'll bring it to life on AWS. When you're finished with this course, you will be able to automate your own cloud infrastructure with the help of CloudFormation, improving the quality of your infrastructure, saving costs by reducing manual work, and increasing the flexibility of your setup. Software required: text editor, SSH client, and AWS account. Download link: http://rapidgator.net/file/5eaa405ad6651e10fcf6b708a18c7f0f/o8tbl.Automating.AWS.with.CloudFormation.rar.html]o8tbl.Automating.AWS.with.CloudFormation.rar.html http://nitroflare.com/view/65CF6A10711E641/o8tbl.Automating.AWS.with.CloudFormation.rar]o8tbl.Automating.AWS.with.CloudFormation.rar http://uploaded.net/file/qcuvjfr4/o8tbl.Automating.AWS.with.CloudFormation.rar]o8tbl.Automating.AWS.with.CloudFormation.rar https://www.bigfile.to/file/b7e45tBZJS8u/o8tbl.Automating.AWS.with.CloudFormation.rar]o8tbl.Automating.AWS.with.CloudFormation.rar Links are Interchangeable - No Password - Single Extraction

Automating AWS with CloudFormation .MP4, AVC, 226 kbps, 1280x720 | English, AAC, 96 kbps, 2 Ch | 1h 19m | 168 MB Instructor: Andreas Wittig Amazon's Cloud is 10 times bigger than its next 10 competitors combined. As an AWS customer, you benefit from a fast-growing and innovative platform. You probably started to manage your cloud infrastructure by clicking through the AWS Management Console. But managing growing AWS environments manually is complex and fault-prone. This course, Automating AWS with CloudFormation, will teach you the skills you need to automate your cloud infrastructure. First, you will learn how to describe your infrastructure in code, also called Infrastructure as Code. Next, you will dive into CloudFormation, which allows you to describe your infrastructure in a template, and finally, you'll bring it to life on AWS. When you're finished with this course, you will be able to automate your own cloud infrastructure with the help of CloudFormation, improving the quality of your infrastructure, saving costs by reducing manual work, and increasing the flexibility of your setup. Software required: text editor, SSH client, and AWS account. DOWNLOAD http://rapidgator.net/file/d46530a2a258a0e5ad89bc27d4c6d1ab/en7lt.Automating.AWS.with.CloudFormation.rar.html http://uploaded.net/file/0ws5xh6k/en7lt.Automating.AWS.with.CloudFormation.rar https://www.bigfile.to/file/yF5BGTMZPTgb/en7lt.Automating.AWS.with.CloudFormation.rar http://nitroflare.com/view/0569B52535D248C/en7lt.Automating.AWS.with.CloudFormation.rar http://uploadgig.com/file/download/89861f3d9d406C08/en7lt.Automating.AWS.with.CloudFormation.rar