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Free Download Udemy - Testing Aiml Models Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 849.76 MB | Duration: 1h 59m QA Pros, SDETs, and Functional Testers-Add AI/ML Testing to Your Skill Set ! ! What you'll learn Upon completing this course, QA , SDET, QA Test Automation professionals will be equipped to Effectively Test and Validate ML Models. Implement ML-Specific API Testing and Automation. Monitor and Manage Models for Ongoing Quality Assurance Ensure Responsible and Ethical AI through Rigorous Testing Requirements This course is designed to be accessible to both beginners and experienced QA professionals looking to expand their expertise into AI and ML testing. To get the most out of this course, here are a few helpful (but not mandatory) prerequisites Basic Understanding of Software Testing Principles. Interest in Machine Learning Concepts. No prior experience with ML is necessary, but a curiosity about how machine learning models work will enhance your learning experience. Familiarity with Testing Tools (Preferred but Not Required) A Laptop or Computer for Hands-On Practice. Description Course Highlights:Manage the end-to-end lifecycle of ML models. Gain the skills to perform functional, early-stage, and post-deployment testing of ML models.Catch issues early with proactive, early-stage testing.Define and automate API testing for ML models. Learn how to design, and automate API testing for machine learning models.Master functional testing to validate model accuracy and behaviour.Uphold responsible AI through dedicated testing methods. Apply ethical testing techniques to identify biases, ensure model transparency, and uphold fairness in ML applications.Set up continuous quality assurance to monitor live ML models.Why This Course?ML Testing Skills Are in High Demand - Be among the few QA specialists with this expertiseStay Relevant in the Evolving Tech Landscape - AI/ML testing isn't just an edge; it's essentialTransform Your Career Prospects - Add powerful, sought-after skills to your profile!Did you know? As AI and ML continue to transform industries, the need for QA professionals who understand how to test ML models is skyrocketing. Traditional QA methods don't cover ML's complexities like data drift, model accuracy, and ethical concerns, making ML testing a must-have skill for any QA professional looking to stay relevant and impactful.If you're looking to add one of the most in-demand skills to your QA skillset, then this course is a must! Overview Section 1: Basics of Machine Learning Model Lecture 1 Intro to AI system. Lecture 2 Introduction and agenda of tutorial. Lecture 3 What is Machine Learning and approaches of machine learning. Section 2: Early Testing in ML Model Modelling or Engineering Phase. Lecture 4 ML Model Lifecycle Offline and Online Modes. Lecture 5 Important Terminologies in ML Model Testing. Lecture 6 Demo- Predicting Energy output of power plant(ML Model). Lecture 7 Supervised Learning and Hyperparamters. Section 3: Unsupervised Learning Models Testing in Modelling phase Lecture 8 Unsupervised learning and types. Section 4: Reinforcement Learning in ML models Lecture 9 Reinforcement Learning in ML models with examples Lecture 10 Top Python Libraries for ML Models. Section 5: Functional Testing of AIML model in Evaluation phase. Lecture 11 Temperature Testing to fine tune the AIML model response Lecture 12 Zero shot prompting Testing. Lecture 13 Chain of Thought Prompting Testing. Lecture 14 Repeatability and Context Management Testing. Section 6: API Automation Lecture 15 Download Postman, create Google Gemini Account and setup env for testing. Lecture 16 PostBot Pluggin to generate automation script for Model API Response. Section 7: Responsible AI Testing with examples. Lecture 17 Responsible AI and Fairness and Bias Detection Testing. Lecture 18 Transparency and Ethical Testing. Lecture 19 Data Security and Privacy Testing. Lecture 20 Societal Impact Testing. Section 8: Post Deployment Testing of AIML Models. Lecture 21 Latency and Drift Testing. Lecture 22 Shadow Testing and Canary Testing of AIML Model. Section 9: ThankYou!! Lecture 23 Thank You Note!! This course is tailored for QA professionals, SDETs, Data Analysts, and anyone involved in quality assurance who wants to expand their skills into the exciting field of AI and Machine Learning (ML) testing. The course content is designed to help you bridge the gap between traditional software testing and the specialized needs of ML model validation, making it valuable for:,Quality Assurance (QA) Engineers looking to enhance their testing toolkit with skills specific to AI/ML model reliability, functionality, and fairness.,Software Development Engineers in Test (SDETs) aiming to stay ahead of the curve by learning how to automate and monitor ML model testing processes.,Functional and Automation Testers interested in developing new testing strategies for ML models and ensuring their robust performance across different environments.,Data Analysts and ML Enthusiasts who want to learn the testing practices that can ensure model accuracy and compliance in production settings. 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Free Download Udemy - Master Communication Models Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 649.05 MB | Duration: 1h 0m Practical Applications for Effective Interaction What you'll learn Understand Key Communication Models: Learn foundational communication models like the Ladder of Inference and how they shape everyday interactions Identify Communication Breakdown Triggers: Recognise common causes of miscommunication and how to address them before they escalate Improve Clarity and Precision:Apply communication models to sharpen your message and ensure that your meaning is clearly understood by others. Enhance Critical Thinking in Conversations: Slow down thought processes and critically assess how you interpret and respond to information Apply Models in Real-World Scenarios:Use communication frameworks to resolve workplace conflicts, improve team collaboration, and boost relationships Adapt Communication for Diverse Settings:Learn to tailor communication strategies for more effective interactions Foster Better Decision-Making Through Communication:by understanding how your thinking affects your communication patterns. Develop Emotional Awareness in Conversations:Strengthen your emotional intelligence by recognising how emotions impact communication and learning to manage them Requirements At least a B2 (upper-intermediate) level of English Description Please be aware that although the overall video length of the course isn't extensive the information and worksheets in the resource section are plentiful! I'm particularly fond of the worksheet: Techniques to help you think rationally and make more objective decisions. This course is the fourth module in the Mastering Effective Communication in Diverse Workplaces series, focusing on communication models for improved interaction. If you've completed modules on emotional intelligence, psychological barriers, and active listening, this next step is designed to help you understand and apply key communication frameworks like the Ladder of Inference.You'll learn how to identify communication breakdowns, explore the psychology behind them, and apply proven models to improve workplace communication. This course offers practical strategies for professionals in multicultural, multilingual, or cross-generational teams. By the end, you'll be able to navigate complex conversations, prevent misunderstandings, and communicate more clearly.Whether you're a manager, team leader, or looking to enhance your interpersonal communication skills, this course gives you the tools to cultivate effective interactions in any setting.While the primary focus is on professional environments, the communication skills you learn can also enhance personal relationships by helping you manage conversations more effectively in any area of life. Whether you're a manager, team leader, or looking to refine your workplace communication skills, this course provides actionable strategies to boost clarity, create stronger connections, and improve collaboration with colleagues, clients, and diverse teams.What You'll Learn: Master key communication models like the Ladder of Inference for workplace success. Recognise and resolve common communication breakdowns in professional settings.Apply communication frameworks to real-world work situations for enhanced impact.Develop strategies for clear, effective communication in diverse professional teams.Take the next step in your career by transforming the way you communicate at work. With expert guidance and practical examples, this course empowers you to foster meaningful interactions, strengthen professional relationships, and create a more productive workplace. These skills will benefit your personal life too. Join today and transform the way you communicate in both work and life!At the end of the course please be sure to let me know if there is anything I can add to make even more useful and practical. Overview Section 1: Introduction Lecture 1 Introduction Section 2: Linear Models of Communication Lecture 2 The Shannon- Weaver Model Lecture 3 Berlo's SCMR Model Section 3: Transactional Model's of Communication Lecture 4 Introduction to Transactional models Lecture 5 Barnlund's Model Lecture 6 Dance's Model Lecture 7 Heis's Model Section 4: Schramm's Communication model Lecture 8 Schramm's Model Section 5: The Ladder of Inference Lecture 9 Why The Ladder of Inference is a great choice Lecture 10 The Ladder of Inference Model Lecture 11 Example 1: The Ladder of Inference Lecture 12 Example 2: The Ladder of Inference Lecture 13 How you can use the ladder Lecture 14 Climbing down the ladder Lecture 15 Case Studies of The Ladder of Inference Lecture 16 Takeaways and Reflections Section 6: End of Course Quiz Aspiring Leaders: Individuals preparing for leadership roles who want to enhance their ability to communicate effectively.,Managers and Team Leaders: Looking to improve their communication skills and better navigate team dynamics.,HR Professionals: Those responsible for fostering communication within teams and resolving conflicts,Project Managers: Professionals managing diverse teams and requiring clear communication to ensure project success.,Individuals Seeking Personal Growth:Anyone looking to develop stronger interpersonal skills and understand communication models,Non-native English Speakers:Professionals working in English who want to improve clarity and communication in the workplace,Consultants and Coaches: Experts who support teams or clients in improving communication and collaboration. 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Free Download Quantization for GenAI Models by Start-Tech Academy Published 10/2024 Created by Start-Tech Academy MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 21 Lectures ( 2h 34m ) | Size: 807 MB Unlock the power of model optimization! Learn how to apply quantization and make your GenAI models efficient with Python What you'll learn Understand model optimization techniques: Pruning, Distillation, and Quantization Learn the basics of data types like FP32, FP16, BFloat16, and INT8 Master downcasting from FP32 to BF16 and FP32 to INT8 Learn the difference between symmetric and asymmetric quantization Implement quantization techniques in Python with real examples Apply quantization to make models more efficient and deployment-ready Gain practical skills to optimize models for edge devices and resource-constrained environments Requirements Basic Python knowledge is recommended, but no prior AI experience is required. Description If you are a developer, data scientist, or machine learning enthusiast who wants to optimize and deploy efficient AI models, this course is for you. Do you want to make your models faster and more resource-efficient while maintaining performance? Are you looking to learn how to apply quantization techniques for better model deployment? This course will teach you how to implement practical quantization techniques, making your models lean and deployable on edge devices.In this course, you will:Learn the core concepts of Quantization, Pruning, and Distillation.Understand different data types like FP32, FP16, BFloat16, and INT8.Explore how to convert FP32 to BF16 and INT8 for efficient model compression.Implement symmetric and asymmetric quantization in Python with real-world applications.Understand how to downcast model parameters from FP32 to INT8 for deployment.Gain hands-on experience with Python-based quantization, making your models suitable for mobile and IoT devices.Why learn quantization? Quantization allows you to reduce the size and computational load of models, making them suitable for resource-constrained devices like smartphones, IoT devices, and embedded systems. By mastering quantization, you can ensure your models are faster, more energy-efficient, and easier to deploy while maintaining accuracy.Throughout the course, you'll learn to implement quantization techniques and optimize your models for real-world applications. This course provides the perfect balance of theory and practical application for making machine learning models more efficient.By the end of the course, you'll have a deep understanding of quantization, and the ability to optimize and deploy efficient models on edge devices. Ready to optimize your AI models for efficiency and performance? Enroll now and start your journey! Who this course is for Beginners in machine learning looking to learn practical model optimization techniques like quantization AI professionals and students wanting to optimize models for deployment on resource-constrained devices Homepage https://www.udemy.com/course/quantization/ Screenshot Rapidgator https://rg.to/file/650f02e9b5b1ad8b23a1e82b4f7e0043/jdifw.Quantization.for.GenAI.Models.rar.html Fikper Free Download https://fikper.com/UD5gJmXWhS/jdifw.Quantization.for.GenAI.Models.rar.html No Password - Links are Interchangeable

Free Download Probability Distribution Models Published 10/2024 Created by Robert (Bob) Steele MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 12 Lectures ( 3h 8m ) | Size: 2.27 GB Mastering the Language of Data: From Distributions to Predictive Models What you'll learnIdentify various data distributions by examining the shape, center, and spread of datasets in real-world scenarios. Explain the significance of different data shapes, including symmetric, skewed, and bimodal distributions, in various contexts. Classify different types of distributions such as Uniform, Poisson, Exponential, and Binomial through theoretical understanding and practical examples. Analyze datasets to determine the appropriate mathematical models and describe their underlying patterns and behaviors. Compare the characteristics of different data distributions and their implications in quantitative analysis. Apply mathematical models to perform quantitative analysis, make predictions, and understand phenomena governing data in real-life situations. Evaluate the accuracy and relevance of different statistical models in the context of real-world applications, such as predicting sales outcomes or analyzing tr Create visual and verbal presentations of data analysis results, demonstrating a thorough understanding of data shapes and mathematical models. RequirementsBasic Mathematical Skills: Familiarity with fundamental mathematical concepts, including basic arithmetic, algebra, and probability. Introductory Statistics: A foundational understanding of basic statistical concepts, such as mean, median, mode, and standard deviation. Analytical Thinking: An ability to engage in logical reasoning and problem-solving to analyze data and interpret results. Computer Literacy: Basic proficiency in using a computer, including the ability to navigate and utilize software tools for data analysis. Interest in Data Analysis: A keen interest in understanding and working with data, as well as a desire to learn about statistical analysis and mathematical modeling. Access to a Computer: Parti[beeep]nts should have access to a computer for completing course exercises and assignments. DescriptionWelcome to a journey through the fascinating world of data shapes and mathematical models! In this course, we will embark on a deep dive into the three pivotal pillars of statistical data analysis: Shape, Center, and Spread, unraveling the mysteries behind diverse data distributions.Starting with the Shape of Data, we will explore how data can be represented through various distributions, emphasizing the significance of recognizing and understanding different data shapes in real-world scenarios. Take the corporate world, for example, where salaries often follow a skewed distribution, or the predictable intervals of atom decay, each presenting unique characteristic distributions. Through practical examples and interactive sessions, we will identify and analyze single-peaked histograms, symmetric, skewed, and bimodal distributions, gaining insights into the intrinsic patterns and behaviors of different datasets.Diving deeper, we will introduce and demystify a range of Mathematical Descriptions of Data Shapes. From the simplicity of Uniform Distributions, seen in rolling a fair die, to the complexity of Poisson Distributions, representing events in fixed intervals, we will traverse the landscape of Exponential and Binomial Distributions, uncovering the intricacies of these mathematical models. Each session will be filled with real-life examples, hands-on exercises, and discussions, ensuring that you not only grasp the theoretical aspects but also develop a practical understanding of these concepts.Our journey does not stop at mere identification and description; we delve into the Importance of Mathematical Models, unraveling how they empower us to perform quantitative analysis, make accurate predictions, and gain a profound understanding of the underlying phenomena governing the data. Whether it's predicting sales outcomes, analyzing traffic patterns, or exploring natural occurrences, you will learn to apply these models confidently and accurately.In conclusion, this course is designed to transform your perspective on data, equipping you with the knowledge and skills to analyze, describe, and predict with precision. Whether you are a student stepping into the world of statistics, a professional looking to sharpen your data analysis skills, or simply a data enthusiast eager to understand the language of numbers, this course is your gateway to mastering the art of deciphering data.Join us on this exhilarating adventure through the world of data shapes and mathematical models, and emerge with the tools and confidence to conquer the realm of statistical analysis! Who this course is forStudents: Those stepping into the world of statistics or pursuing degrees in fields such as mathematics, data science, economics, engineering, or social sciences. Professionals: Individuals working in fields where data analysis is essential, such as marketing, finance, business analytics, healthcare, and research, looking to sharpen their data analysis skills. Data Enthusiasts: Anyone with a keen interest in understanding and interpreting data, regardless of their professional background. Researchers: Academics and scientists who need to analyze data as part of their research work and wish to deepen their understanding of statistical methods. Educators: Teachers and instructors who teach statistics or data analysis and want to enhance their teaching methodologies with a deeper understanding of data shapes and mathematical models. Career Changers: Individuals looking to transition into data-related roles and seeking to build a solid foundation in statistical data analysis. Decision Makers: Managers and executives who want to leverage data-driven insights to inform business strategies and decisions. 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Free Download Introduction To Machine Learning Models (Ai) Testing Published 10/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 3.01 GB | Duration: 4h 54m From Scratch, Learn testing types and Strategies involved in all the phases of ML Models (AI) with real time examples What you'll learnIntroduction to Artificial Intelligence and Machine Learning Models Understanding Lifecycle of Machine Learning Models and their testing Scope Shift-Left Testing in the ML Engineering Phase such as OverFitting & UnderFitting Testing QA Functional Testing in the ML Validation Phase with 25 different Testing types & Strategies API Testing Scope for Machine Learning Models with ChatGPT Model example Responsible AI Testing for Machine Learning Models such as Bias, Fairness, Ethical, Privacy Testing etc Post-Deployment Testing Strategies for ML Models such as DataDrift & Concept Drift testing Continuous Tracking and Monitoring Activities for QA in Production RequirementsNone. All the concepts are taken care with Scratch explanation DescriptionThis course will introduce you to the World of Machine Learning Models Testing. As AI continues to revolutionize industries, many companies are developing their own ML models to enhance their business operations. However, testing these models presents unique challenges that differ from traditional software testing. Machine Learning Model testing requires a deeper understanding of both data quality and model behavior, as well as the algorithms that power them.This Course starts with explaining the fundamentals of the Artificial Intelligence & Machine Learning concepts and gets deep dive into testing concepts & Strategies for Machine Learning models with real time examples.Below is high level of Agenda of the tutorial:Introduction to Artificial IntelligenceOverview of Machine Learning Models and their LifecycleShift-Left Testing in the ML Engineering PhaseQA Functional Testing in the ML Validation PhaseAPI Testing Scope for Machine Learning ModelsResponsible AI Testing for ML ModelsPost-Deployment Testing Strategies for ML ModelsContinuous Tracking and Monitoring Activities for QA in ProductionBy the end of this course,you will gain expertise in testing Machine Learning Models at every stage of their lifecycle.Please Note:This course highlights specialized testing types and methodologies unique to Machine Learning Testing, with real-world examples.No specific programming language or code is involved in this tutorial. OverviewSection 1: Getting Started with Machine Learning Testing basics Lecture 1 Introduction and Agenda of the tutorial Lecture 2 Introduction to Artificial Intelligence Systems with examples Lecture 3 What is Machine Learning and how it is related to Artificial Intelligence family Lecture 4 Examples of commonly used Machine Learning Models and their usage Section 2: Shift Left Testing in ML Model Engineering phase (Supervised Learning) Lecture 5 Understand Machine Learning Model Life cycle stages with online/offline modes Lecture 6 How Machine Learning models works in nutshell -Learn terminologies used Lecture 7 Understand how OverFitting Testng & UnderFitting works with Trained data sets Lecture 8 Predicting House Prices (ML Model) Demo to show how internally Algorithms works Lecture 9 Revision on Supervised Learning Model Testing with Overfitting/UnderFitting ex Section 3: Unsupervised Learning Models Testing in Engineering Phase Lecture 10 Introduction to Unsupervised Learning in the ML models with example Lecture 11 Testing scope on Unsupervised Learning with Data point patterns&Cluster scores Lecture 12 Revision on Unsupervised Learning with cluster score analysis Section 4: Reinforcement Learning & Commonly used Frameworks and Algos in ML Models Lecture 13 Introduction to Reinforcement Learning in ML Model with examples Lecture 14 Algorithms and Frameworks commonly used in developing ML Models Section 5: Functional Testing for Machine Learning Models in Evaluation Phase Lecture 15 What are Validation Unseen Data sets and why it is required Lecture 16 Temperature Testing to fine tune the response predictions from ML Models Lecture 17 Prompts Testing with Zero Shot & Chain of thought Prompts test Lecture 18 Relevance stary Testing & Fantasy claims testing on ML Models Lecture 19 Repeatability Testing & Asking question in different phases to test Lecture 20 Style Transfer testing & Intent recognition testing on ML Models Lecture 21 What is Invariance Testing & BiDirectional testing for AI Models Section 6: Introduction to API Testing on Machine Learning Models Lecture 22 Create OpenAI Account to test ChatGPT API's of generating response Lecture 23 Download Postman tool to setup ChatGPT APIs environment for testing Lecture 24 PostBot plugin to generate automation scripts for API responses in Postman Section 7: Responsible AI Testing with examples on Machine Learning (AI) Models Lecture 25 Importance of Fairness testing on ML responses to check bias Lecture 26 Transparency testing and why it is necessary to stay ahead in AI competition Lecture 27 Data Privacy and Security testing on Machine Learning models Section 8: Post Deployment Testing Types with examples on Machine Learning Models Lecture 28 Importance of Integration & Latency testing on Production ML models Lecture 29 Importance of Data drift Testing & Concept Drift Testing in ML Models Lecture 30 Shadow Testing & A/B Testing to certify the latest version of ML into prod Section 9: Final words - Impact of Machine Learning Models in QA Space Lecture 31 How QA's can be critical resources for Machine Learning Model Life cycle Lecture 32 Bonus Lecture QA Testers,Software Engineers,Software Testers,Data Engineers,Developers,Test Managers Homepage https://www.udemy.com/course/machine-learning-models-ai-testing/ Rapidgator https://rg.to/file/0274d5b78f2c1dc209d45da2779adba2/ljrfw.Introduction.To.Machine.Learning.Models.Ai.Testing.part4.rar.html https://rg.to/file/0398e5d870f0349257e96e5572208a39/ljrfw.Introduction.To.Machine.Learning.Models.Ai.Testing.part1.rar.html https://rg.to/file/7248aaf3582e508835ebdf9a50a0ee13/ljrfw.Introduction.To.Machine.Learning.Models.Ai.Testing.part2.rar.html https://rg.to/file/cd83cdb364cc92fbdda0c244d064661d/ljrfw.Introduction.To.Machine.Learning.Models.Ai.Testing.part3.rar.html Fikper Free Download https://fikper.com/7YbU88WFvn/ljrfw.Introduction.To.Machine.Learning.Models.Ai.Testing.part1.rar.html https://fikper.com/Iwf11shZXn/ljrfw.Introduction.To.Machine.Learning.Models.Ai.Testing.part3.rar.html https://fikper.com/cF8XUqYGTE/ljrfw.Introduction.To.Machine.Learning.Models.Ai.Testing.part4.rar.html https://fikper.com/yhyAnByfdB/ljrfw.Introduction.To.Machine.Learning.Models.Ai.Testing.part2.rar.html No Password - Links are Interchangeable

Free Download Enterprise AI Development with GitHub Models and Azure Released 10/2024 With Rob Bos MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 2h 23m 38s | Size: 300 MB Learn how to prototype applications with GitHub Models before deploying your code to Azure for production. Course details GitHub Models is a great place for developers to experiment with large language models (LLMs), especially if you're an Azure developer who's looking to test an idea or prototype an application. Integrating GitHub Models with Azure allows you to move logic back and forth as you work through each phase of a project. In this course, instructor Rob Bos shows you how to create prototypes and development paths in GitHub Models and then scale them for deployment in Azure. Along the way, gather insights to help you leverage the power of planning and practice, shifting your attention away from the more constrained options of GitHub Models to the more open and flexible features offered by Azure. This course is an ideal fit for Azure developers looking for a quick start guide to GitHub Models. Homepage https://www.linkedin.com/learning/enterprise-ai-development-with-github-models-and-azure Screenshot Rapidgator https://rg.to/file/2303f568970e1a1d17e5ba81ce58a448/pyyju.Enterprise.AI.Development.with.GitHub.Models.and.Azure.rar.html Fikper Free Download https://fikper.com/JEyzlmecQH/pyyju.Enterprise.AI.Development.with.GitHub.Models.and.Azure.rar.html No Password - Links are Interchangeable

Free Download Build, Train and Deploy ML Models with Keras on Google Cloud Released 10/2024 By Google Cloud MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + subtitle | Duration: 1h 51m | Size: 193 MB This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use. This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use. Homepage https://www.pluralsight.com/courses/tensorflow-google-cloud-3 Screenshot Rapidgator https://rg.to/file/8f1079499ff5d6224ab8f09f0b0ca6e6/rydlb.Build.Train.and.Deploy.ML.Models.with.Keras.on.Google.Cloud.rar.html Fikper Free Download https://fikper.com/ZLd8Yb2eNX/rydlb.Build.Train.and.Deploy.ML.Models.with.Keras.on.Google.Cloud.rar.html No Password - Links are Interchangeable

Free Download Best Practices for Integrating GitHub Models Released 10/2024 With Noah Gift, Pragmatic AI Labs MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 12m 26s | Size: 201 MB Learn best practices for the new GitHub models. Learn best practices for the new GitHub models. Course details With the launch of GitHub Models, GitHub is enabling more than 100 million developers to become AI engineers and build with industry-leading AI models. This course with instructor Alfredo Deza provides best practices for using this new integration. Learn solid approaches for working with GitHub's new generative AI service. Alfredo covers key strategies for integrating machine learning models into your projects efficiently. This course is aimed at developers looking to improve their GitHub Models workflow and enhance AI-driven projects, with topics including marketplace navigation, responsible AI implementation, resource management, and application development. Note: This course was created by Pragmatic AI Labs. We are pleased to host this training in our library. Homepage https://www.linkedin.com/learning/best-practices-for-integrating-github-models-24686904 Rapidgator https://rg.to/file/364dec5f13fc49434c5bd99a4a2b66db/gtgex.Best.Practices.for.Integrating.GitHub.Models.rar.html Fikper Free Download https://fikper.com/SGGq6Bnlju/gtgex.Best.Practices.for.Integrating.GitHub.Models.rar.html No Password - Links are Interchangeable

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Free Download Understanding and Implementing Data Models with Sisense Duration: 1h 31m | Video: .MP4, 1920x1080 30 fps | Audio: AAC, 32kHz, 2ch | Size: 200 MB Genre: eLearning | Language: English Understanding and Implementing Data Models in Sisense will make you comfortable in connecting to data sources and building data-model. In this course, Understanding and Implementing Data Models in Sisense, you'll learn techniques to build data-model. First, you'll explore connecting to various data sources. Next, you'll discover combining data. Finally, you'll learn how to apply data model techniques. When you're finished with this course, you'll have the skills and knowledge of data model needed to build elasticube. Homepage https://www.pluralsight.com/courses/understanding-implementing-data-models-sisense TakeFile https://takefile.link/e5c8nv26vcvj/qqfyr.Understanding.and.Implementing.Data.Models.with.Sisense.rar.html Rapidgator https://rg.to/file/ce04715951b8c58c37a77acf38623ba7/qqfyr.Understanding.and.Implementing.Data.Models.with.Sisense.rar.html Fikper Free Download https://fikper.com/YKKNnQdpAw/qqfyr.Understanding.and.Implementing.Data.Models.with.Sisense.rar No Password - Links are Interchangeable

Free Download Train OpenSource Large Language Models from Zero to Hero Published 9/2024 Created by Gal Peretz MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English | Duration: 27 Lectures ( 2h 35m ) | Size: 2 GB How to train Open Source LLMs with LoRA QLoRA, DPO and ORPO. What you'll learn: What is language model and how the training pipeline looks like Fine tuning LLMs with supervised fine-tune (LoRA, QLoRA, DoRA) Align LLMs to human preference using DPO, KTO and ORPO Accelerate LLM training with multiple GPUs training and Unsloth library Requirements: No prior knowledge is required Description: Unlock the full potential of Large Language Models (LLMs) with this comprehensive course designed for developers and data scientists eager to master advanced training and optimization techniques.I'll cover everything from A to Z, helping developers understand how LLMs works and data scientists learn simple and advance training techniques. Starting with the fundamentals of language models and the transformative power of the Transformer architecture, you'll set up your development environment and train your first model from scratch.Dive deep into cutting-edge fine-tuning methods like LoRA, QLoRA, and DoRA to enhance model performance efficiently. Learn how to improve LLM robustness against noisy data using techniques like Flash Attention and NEFTune, and gain practical experience through hands-on coding sessions.The course also explores aligning LLMs to human preferences using advanced methods such as Direct Preference Optimization (DPO), KTO, and ORPO. You'll implement these techniques to ensure your models not only perform well but also align with user expectations and ethical standards.Finally, accelerate your LLM training with multi-GPU setups, model parallelism, Fully Sharded Data Parallel (FSDP) training, and the Unsloth framework to boost speed and reduce VRAM usage. By the end of this course, you'll have a good understanding and practical experience to train, fine-tune, and optimize robust open-source LLMs. Who this course is for: Developers, Data scientists, AI enthusiasts Homepage https://www.udemy.com/course/train-opensource-large-language-models-from-zero-to-hero/ Rapidgator https://rg.to/file/88314836bb5c8963acb7be6dc450ff00/niiyo.Train.OpenSource.Large.Language.Models.from.Zero.to.Hero.part1.rar.html https://rg.to/file/2bbb03f4ff4053cdf64789f10bee6da5/niiyo.Train.OpenSource.Large.Language.Models.from.Zero.to.Hero.part2.rar.html https://rg.to/file/0fb79709b9f3a1d86b3fce358e05844a/niiyo.Train.OpenSource.Large.Language.Models.from.Zero.to.Hero.part3.rar.html Fikper Free Download https://fikper.com/Nyigq5O9tB/niiyo.Train.OpenSource.Large.Language.Models.from.Zero.to.Hero.part1.rar.html https://fikper.com/wSWwIftix8/niiyo.Train.OpenSource.Large.Language.Models.from.Zero.to.Hero.part2.rar.html https://fikper.com/p4JuocHbye/niiyo.Train.OpenSource.Large.Language.Models.from.Zero.to.Hero.part3.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 and Open Source Models - Hands-On Practice with Hugging Face Models Released 9/2024 MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Skill Level: Intermediate | Genre: eLearning | Language: English + srt | Duration: 1h 52m | Size: 333 MB Large language models (LLMs) are becoming increasingly crucial in various industries. This course with instructor Harpreet Sahota offers a deep dive into the inner workings of text generation using LLMs. Learn about the importance of tokenization, special tokens, and chat templates in text generation. Explore how to manipulate the next selected token and gain a technical and intuitive understanding of generation parameters such as temperature, top-p, top-k, repetition penalty, length penalty, and bad words list. Discover how these parameters can be combined to form powerful decoding strategies, including greedy search, multinomial sampling, beam search, and contrastive search. Gain hands-on experience using the Hugging Face text generation API and get a sneak peek into interacting with the NVIDIA NIM API to explore larger models. By the end of this course, you'll have a solid foundation in controlling text generation with LLMs, enabling you to apply these skills in real-world scenarios. Homepage https://www.linkedin.com/learning/generative-ai-and-open-source-models-hands-on-practice-with-hugging-face-models TakeFile https://takefile.link/m010gg9mbx6i/myezw.Generative.AI.and.Open.Source.Models.HandsOn.Practice.with.Hugging.Face.Models.rar.html Rapidgator https://rg.to/file/1a4c8075065ffce0c4a9e99a7fb138b7/myezw.Generative.AI.and.Open.Source.Models.HandsOn.Practice.with.Hugging.Face.Models.rar.html Fikper Free Download https://fikper.com/r5rBMTaW1H/myezw.Generative.AI.and.Open.Source.Models.HandsOn.Practice.with.Hugging.Face.Models.rar.html No Password - Links are Interchangeable

Free Download Introduction to GitHub Models By Alfredo Deza Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 1h 13m | Size: 510 MB Video description Introduction to GitHub Models An easy course for getting started and building with GitHub Models This practical course guides you through the process of effectively integrating and using GitHub Models in your projects. You'll start by learning the fundamentals of AI models and understanding the current challenges in the field. The course then walks you through navigating the GitHub Models Marketplace and applying playground techniques to get hands-on experience. You'll explore key features of responsible AI and learn strategic implementation techniques, including how to manage rate limits and scale beyond the free tier. The course also covers GitHub Codespaces, teaching you how to effectively manage resources in this cloud-based development environment. In the final section, you'll dive into best practices for building applications with GitHub Models. This includes creating a Personal Access Token, setting up your development environment, and creating an HTTP API. You'll also learn strategies for testing and validating your implementations. By the end of this course, you'll have a solid understanding of how to integrate GitHub Models into your projects efficiently and responsibly. Whether you're a developer looking to expand your AI toolkit or a project manager aiming to leverage AI in your applications, this course provides the knowledge and skills you need to get started with GitHub Models. About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. Before getting into technology he parti[beeep]ted in the 2004 Olympic Games and was the first-ever World Champion in High Jump representing Peru. He currently works in Developer Relations at Microsoft and is an Adjunct Professor at Duke University teaching Machine Learning, Cloud Computing, Data Engineering, Python, and Rust. With Alfredo's guidance, you will gain the knowledge and skills to build applications from scratch using GitHub Models. TakeFile https://takefile.link/lt20usxtv7z6/trkiv.Introduction.to.GitHub.Models.rar.html Rapidgator https://rg.to/file/1a68da90e2ce9415d6235d1a858d04f2/trkiv.Introduction.to.GitHub.Models.rar.html Fikper Free Download https://fikper.com/lX8fg0QVY2/trkiv.Introduction.to.GitHub.Models.rar.html No Password - Links are Interchangeable

epub | 19.03 MB | English| Isbn:9781936801411 | Author: Douglas Johnson, Maureen Johnson | Year: 2016 Description: Category:Art, Architecture & Photography, Art - History & Criticism, General & Miscellaneous Art, Art Reference https://ddownload.com/oyrkua3yk825 https://rapidgator.net/file/a8766ac9124f312bd7378632af6bd4b4/ https://turbobit.net/8jil8oila9ys.html

Free Download Chatgpt O1 Models From Openai - Ai For Complex Workflows Published 9/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.00 GB | Duration: 1h 2m Introducing ChatGPT- Leveraging o1-Preview, o1-Mini, GPT-4o, and DALL·E 3 for Productivity, Research, and Creativity What you'll learn Beginner's understanding of ChatGPT and Dall-E 3 Differentiating the OpenAI o1 o1-preview and o1-mini Models Using ChatGPT o1 For Research and Productivity Using ChatGPT o1-mini to create a hierarchical technical glossary Creating and editing images with Dall-E 3 Requirements A PC or laptop with internet connection To apply the o1-preview and o1-mini models a paid subscription to ChatGPT is required No experience is required - absolute beginners welcome Description Course Title: Understanding ChatGPT: Leveraging o1-Preview, o1-Mini, GPT-4o, and DALL·E 3 for Productivity, Research, and CreativityCourse Overview:Dive into the forefront of AI technology with this comprehensive course focused on OpenAI's latest models-o1-preview and o1-mini. Designed for professionals, researchers, and creatives, this program explores how to maximize productivity, enhance research capabilities, and unleash creativity using ChatGPT and DALL·E 3. Learn to navigate rate limitations effectively and compare different models to optimize your AI experience.Course Outline:Competence 1: Introduction to OpenAI's o1 SeriesUnderstanding the Evolution: From GPT-4o to o1-preview and o1-miniEnhanced Reasoning Capabilities: What sets the o1 series apartNavigating Rate Limits: Strategies to maximize 30 prompts per weekModel Comparisons: Strengths and use-cases for o1-preview, o1-mini, and GPT-4oCompetence 2: Boosting Productivity with ChatGPTEffective Prompt Engineering: Crafting questions for optimal responsesAutomating Tasks: Using o1-mini for creating video timestampsTime Management: Leveraging AI to streamline daily activitiesCompetence 3: Advanced Research TechniquesComplex Problem Solving: Utilizing o1-preview for in-depth analysisCase Study: Understanding tariff policy in election campaignsEconomic perspectives and implicationsPolitical strategies and communicationData Interpretation: Analyzing and synthesizing information with AI assistanceCompetence 4: Unleashing Creativity with DALL·E 3Introduction to DALL·E 3: Capabilities and applicationsImage Creation: Generating complementary visuals for contentImage Editing: Refining and customizing imagesCompetence 5: Developing a Detailed Communication StrategyStrategic Planning: Crafting messages with AI insightsAudience Analysis: Tailoring content for specific demographicsMulti-Channel Communication: Coordinating across platformsCourse Outcomes:Master the use of o1-preview and o1-mini models for diverse applicationsEnhance research capabilities in economics and political scienceCreate and edit compelling images using DALL·E 3Develop effective communication strategies with AI assistanceOptimize the use of limited prompts to maintain productivityWho Should Enroll: Professionals, researchers, marketers, and creatives eager to harness the power of advanced AI models for practical and innovative applications Overview Section 1: Introduction Lecture 1 Introduction Section 2: Introduction to ChatGPT o1 Models from OpenAI and Core Capabilities Lecture 2 Demonstration of the performance of the new models Lecture 3 Differentiating the OpenAI o1 o1-preview and o1-mini Models Lecture 4 Getting Started with OpenAI's ChatGPT accounts Lecture 5 ChatGPT o1 For Research and Productivity Lecture 6 Using ChatGPT o1-mini to create a hierarchy technical glossary Lecture 7 Sharing ChatGPT outputs with colleagues Section 3: Using Dall-E 3 to create imagery and to edit created images Lecture 8 Creating an image with Dall-E 3 Lecture 9 An Introduction to editing images with Dall-E 3 Section 4: Advanced Creative Processes and Techniques to use with the o1 Models Lecture 10 Creating a Detailed Communication Strategy in o1-preview Lecture 11 Creative Iteration Tactics when using the o1 and 4o models Lecture 12 Establishing Preferences for Creativity and Verbosity (Wordiness) Lecture 13 Creating Youtube Timestamps Learners who want to understand the most powerful AI Large Language Models,Researchers wanting to conduct in depth research into subjects at a very high level,Marketers and Advertisers who want to use AI to improve productivity and get creative inspiration,Small business owners who want to understand how toi use advances in AI to cut costs and to improve productivity,Students who need to complete complex research Homepage https://www.udemy.com/course/chatgpt-o1-models-for-ai-productivity-research-and-creativity/ Rapidgator https://rg.to/file/4dad691275687f37e96dd30a276bd3f3/dbwrm.Chatgpt.O1.Models.From.Openai..Ai.For.Complex.Workflows.part1.rar.html https://rg.to/file/e20ab1006f921b571456dc40803c5d06/dbwrm.Chatgpt.O1.Models.From.Openai..Ai.For.Complex.Workflows.part2.rar.html Fikper Free Download https://fikper.com/k31vMOUrpm/dbwrm.Chatgpt.O1.Models.From.Openai..Ai.For.Complex.Workflows.part1.rar.html https://fikper.com/EdHUmM2RcI/dbwrm.Chatgpt.O1.Models.From.Openai..Ai.For.Complex.Workflows.part2.rar.html No Password - Links are Interchangeable

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Woba Models - Issue 12 2024 English | 80 pages | PDF | 37 MB https://rapidgator.net/file/fe43ff005573cba1c61f72a1e4896c42/ https://nitroflare.com/view/2817E7A6BA15D52/

Managing Taxonomy with SharePoint, PowerShell, and Object Models MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hours | 173 MB Genre: eLearning | Language: English More ways to generate workflows for SharePoint 2013. You can't have too many workflows...nor too many tools to create them! Download link: http://rapidgator.net/file/bc8269c934dac37df23f3b5680926273/cwhit.Managing.Taxonomy.with.SharePoint.PowerShell.and.Object.Models.rar.html http://nitroflare.com/view/E9B4865DA5D821D/cwhit.Managing.Taxonomy.with.SharePoint.PowerShell.and.Object.Models.rar https://uploadgig.com/file/download/d4B8a562c8251904/cwhit.Managing.Taxonomy.with.SharePoint.PowerShell.and.Object.Models.rar http://uploaded.net/file/mg5kge9c/cwhit.Managing.Taxonomy.with.SharePoint.PowerShell.and.Object.Models.rar Links are Interchangeable - No Password - Single Extraction

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O'Reilly - Introduction to Deep Learning Models With TensorFlow English | Size: 162.29 MB Category: Tutorial Learn How to Work With TensorFlow to Create and Run a TensorFlow Graph, and Build a Deep Learning Model. TensorFlow is by far the most popular deep learning software package available today. This training covers all of the essentials of TensorFlow; and provides you with hands-on experience building a deep learning model using the TensorFlow library. Every line of code written during the course is analyzed to help you understand what can be a complicated process. The lessons look at the key mathematical foundations of deep learning models, giving you insight into what makes these techniques work. Created for software engineers and budding data scientists, the course requires basic familiarity with Python programming; as well as statistics concepts such as linear and logistic regression, machine learning concepts like classification, and linear algebra. Jupyter Notebook is used to write and run code. * Learn how to set up TensorFlow on your machine * Master the ability to build a deep learning model that solves true-to-life problems * Understand how to create and run a TensorFlow graph * Understand the benefits of deep learning compared to traditional machine learning and when it should be used * Become familiar with the "gotchas" of the TensorFlow library * Learn how to debug programs when things go wrong Download link: http://rapidgator.net/file/2de85c8c8c48e4c9f23a2adb4bb741dd/y0z2i.OReilly..Introduction.to.Deep.Learning.Models.With.TensorFlow.rar.html http://nitroflare.com/view/768348B72004AF7/y0z2i.OReilly..Introduction.to.Deep.Learning.Models.With.TensorFlow.rar https://uploadgig.com/file/download/dD52647986d43Ba3/y0z2i.OReilly..Introduction.to.Deep.Learning.Models.With.TensorFlow.rar http://uploaded.net/file/0z3ynsls/y0z2i.OReilly..Introduction.to.Deep.Learning.Models.With.TensorFlow.rar Links are Interchangeable - No Password - Single Extraction

269 models English | Size: 9.3GB Category: Assets Right as with the 200 models uploaded earlier, no preview image. All preview images are in the PREVIEWS folder and this is not archived, so grab that to see what is included. As I have a lot of work on right now, I did not have the time to tidy this lot up or rename stuff. It was originally supposed to be 300 models, however on checking it, I discovered that models 226-255 and model 455 are not included, hence the title 260 models There is no single preview image as before, so please don't go to the forum thread and see that image of 16 models and post it here. 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CGAxis Models Volume 55 3D Medical English | Size: 492.6MB Category: Assets In this collection you can find many kinds of 3d stuff like: stethoscope, hospital table, rehabilitation walker, wheelchair, operating lamp, operating table, hospital bed and many others. It contains 26 highly detailed 3d models. Each of them is mapped and textured if diffuse, bump or reflect map are used. Others have prepared materials with diffuse color and reflect set properly. Materials are prepared for 3ds max 2010 or higher (VRay, Mental Ray, Scanline) and Cinema 4D 11 or higher (Advanced Renderer, VRay). You can also download this collection in FBX and OBJ file formats in which models are also mapped. CGAxis Models Volume 55 3D Medical is perfect if you are going to make a project of hospital interiors. AVAILABLE FILE FORMATS: * 3ds max VRay (3ds Max 2010 or higher) * 3ds max Mentalray (3ds Max 2010 or higher) * Cinema 4D (Cinema 4D 11 or higher) * Cinema 4D VRay (Cinema 4D 11 or higher) * FBX * OBJ SPECIFICATION: Total size: 1.22 GB Textures: Yes Materials: Yes Shipping: Downloadable This collection does not include scene presented in render image. Download link: http://rapidgator.net/file/b791849e4cad787e71082a62b38a493e/0pwaw.CGAxis.Models.Volume.55.3D.Medical.rar.html]0pwaw.CGAxis.Models.Volume.55.3D.Medical.rar.html http://nitroflare.com/view/DC5361454C79786/0pwaw.CGAxis.Models.Volume.55.3D.Medical.rar]0pwaw.CGAxis.Models.Volume.55.3D.Medical.rar http://uploaded.net/file/07cehtsr/0pwaw.CGAxis.Models.Volume.55.3D.Medical.rar]0pwaw.CGAxis.Models.Volume.55.3D.Medical.rar https://www.bigfile.to/file/WzYDksJmtm7a/0pwaw.CGAxis.Models.Volume.55.3D.Medical.rar]0pwaw.CGAxis.Models.Volume.55.3D.Medical.rar Links are Interchangeable - No Password - Single Extraction

CGAxis Models Volume 46 3D Windows English | Size: 449.7MB Category: Assets CGAxis Models Volume 46 - 3D Windows is a collection contains 50 highly detailed 3D models of metal, wooden, and plastic windows in many dimensions. Now you don't have to loose your time to modelling windows, you can simply add your favorite window to your project from our catalog. All are mapped and have materials and textures. Compatible with 3ds max 2010 or higher and many others. AVAILABLE FORMATS: * max VRay (3ds max 2010 or higher) * max Mentalray (3ds max 2010 or higher) * max Scanline (3ds max 2010 or higher) * Cinema 4D (Cinema 4D 11 or higher) * Cinema 4D VRay (Cinema 4D 11 or higher) * FBX * OBJ Download link: http://rapidgator.net/file/4bfdbff970137c790058e03f0267cefb/644jg.CGAxis.Models.Volume.46.3D.Windows.rar.html]644jg.CGAxis.Models.Volume.46.3D.Windows.rar.html http://nitroflare.com/view/A9403A5631A27AB/644jg.CGAxis.Models.Volume.46.3D.Windows.rar]644jg.CGAxis.Models.Volume.46.3D.Windows.rar http://uploaded.net/file/sgn0cb6p/644jg.CGAxis.Models.Volume.46.3D.Windows.rar]644jg.CGAxis.Models.Volume.46.3D.Windows.rar https://www.bigfile.to/file/y8DtnXDG8nr9/644jg.CGAxis.Models.Volume.46.3D.Windows.rar]644jg.CGAxis.Models.Volume.46.3D.Windows.rar Links are Interchangeable - No Password - Single Extraction

Pluralsight - Clean View Models With Assisticant English | MP4 | AVC 413kbps | 1024x768 | 15fps | 3h 12mins | AAC stereo 124kbps | 632 Mb Genre: eLearning This course demonstrates how to create clean, declarative view models that don't explicitly raise property changed events or use a message bus. A view model should read like a user interface specification. Most view models, however, are too busy raising property changed events or sending and subscribing to a message bus. This course will give you the tools and patterns you need to write clean, declarative code for WPF, Windows Phone, and Windows Store clients. A clean view model does one thing, and one thing only; the open source Assisticant library will handle the rest. DOWNLOAD http://rapidgator.net/file/93e1f339b55c48db9948376ae3fca895/9Models.part1.rar.html http://rapidgator.net/file/3ba031dd20f91919302b35f8ad070ced/9Models.part2.rar.html http://rapidgator.net/file/b22237b02aa620c41d89c5d5db1484de/9Models.part3.rar.html http://rapidgator.net/file/760b442362b22f5d6b78cb9bfd82007f/9Models.part4.rar.html http://rapidgator.net/file/02c07ee9234cb5e46dacaf5c93432320/9Models.part5.rar.html http://rapidgator.net/file/13f8e7dba1777b8b57466d035860caf0/9Models.part6.rar.html http://rapidgator.net/file/52f03873a391daa17b8d9fab3c8dcad9/9Models.part7.rar.html http://uploaded.net/file/df2qotxm/9Models.part1.rar http://uploaded.net/file/69ku5bmr/9Models.part2.rar http://uploaded.net/file/v19ccukr/9Models.part3.rar http://uploaded.net/file/oomg546o/9Models.part4.rar http://uploaded.net/file/sntjz78e/9Models.part5.rar http://uploaded.net/file/jj1k6cb6/9Models.part6.rar http://uploaded.net/file/3l4vosx8/9Models.part7.rar http://www.hitfile.net/11wB/9Models.part1.rar.html http://www.hitfile.net/11lU/9Models.part2.rar.html http://www.hitfile.net/11h9/9Models.part3.rar.html http://www.hitfile.net/12gP/9Models.part4.rar.html http://www.hitfile.net/12Fo/9Models.part5.rar.html http://www.hitfile.net/11qE/9Models.part6.rar.html http://www.hitfile.net/127X/9Models.part7.rar.html http://www.uploadable.ch/file/Tq6PYqKDsa9y/9Models.part1.rar http://www.uploadable.ch/file/F4CtGXSpnzWk/9Models.part2.rar http://www.uploadable.ch/file/pexfdwrU4ZAE/9Models.part3.rar http://www.uploadable.ch/file/KFYyY79HkvZn/9Models.part4.rar http://www.uploadable.ch/file/PcFyUrER4dpW/9Models.part5.rar http://www.uploadable.ch/file/XwD9TpAzRQMK/9Models.part6.rar http://www.uploadable.ch/file/ByZ8kdsyaK7z/9Models.part7.rar