Ultimate Machine Learning With Ml Net Build Optimize And Deploy Powerful Machine Learning Models For Data Driven Insights With Ml Net Azure Functions And Web Api
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Ultimate Machine Learning with ML.NET: Build, Optimize, and Deploy Powerful Machine Learning Models for Data-Driven Insights with ML.NET, Azure Functions, and Web API
Author: Kalicharan Mahasivabhattu
language: en
Publisher: Orange Education Pvt Limited
Release Date: 2024-06-30
“Empower Your .NET Journey with Machine Learning” Key Features● Step-by-step guidance to help you navigate through various machine learning tasks and techniques with ML.NET. ● Explore all aspects of ML.NET, from installation and configuration to model deployment. ● Engage in practical exercises and real-world projects to solidify your understanding. Book DescriptionDive into the world of machine learning for data-driven insights and seamless integration in .NET applications with the Ultimate Machine Learning with ML.NET. The book begins with foundations of ML.NET and seamlessly transitions into practical guidance on installing and configuring it using essential tools like Model Builder and the command-line interface. Next, it dives into the heart of machine learning tasks using ML.NET, exploring classification, regression, and clustering with its versatile functionalities. It will delve deep into the process of selecting and fine-tuning algorithms to achieve optimal performance and accuracy. You will gain valuable insights into inspecting and interpreting ML.NET models, ensuring they meet your expectations and deliver reliable results. It will teach you efficient methods for saving, loading, and sharing your models across projects, facilitating seamless collaboration and reuse. The final section of the book covers advanced techniques for optimizing model accuracy and refining performance. You will be able to deploy your ML.NET models using Azure Functions and Web API, empowering you to integrate machine learning solutions seamlessly into real-world applications. What you will learn ● Understand the basics of ML.NET and its capabilities in the machine learning landscape. ● Gain practical experience with the ML.NET Model Builder and command-line interface (CLI) to efficiently create models. ● Understand how to choose the most suitable algorithms and fine-tune them for optimal performance within ML.NET. Table of Contents1. Introduction to ML.NET 2. Installing and Configuring ML.NET 3. ML.NET Model Builder and CLI 4. Collecting and Preparing Data for ML.NET 5. Machine Learning Tasks in ML.NET 6. Choosing and Tuning Machine Learning Algorithms in ML.NET 7. Inspecting and Interpreting ML.NET Models 8. Saving and Loading Models in ML.Net 9. Optimizing ML.NET Models for Accuracy 10. Deploying ML.NET Models with Azure Functions and Web API Index
Ultimate Machine Learning with ML.NET:
Author: Kalicharan Mahasivabhattu
language: en
Publisher: Orange Education Pvt Ltd
Release Date: 2024-06-30
TAGLINE “Empower Your .NET Journey with Machine Learning” KEY FEATURES ● Step-by-step guidance to help you navigate through various machine learning tasks and techniques with ML.NET. ● Explore all aspects of ML.NET, from installation and configuration to model deployment. ● Engage in practical exercises and real-world projects to solidify your understanding. ● Learn how to optimize, tune, and interpret your ML.NET models for maximum accuracy and performance. DESCRIPTION Dive into the world of machine learning for data-driven insights and seamless integration in .NET applications with the Ultimate Machine Learning with ML.NET. The book begins with foundations of ML.NET and seamlessly transitions into practical guidance on installing and configuring it using essential tools like Model Builder and the command-line interface. Next, it dives into the heart of machine learning tasks using ML.NET, exploring classification, regression, and clustering with its versatile functionalities. It will delve deep into the process of selecting and fine-tuning algorithms to achieve optimal performance and accuracy. You will gain valuable insights into inspecting and interpreting ML.NET models, ensuring they meet your expectations and deliver reliable results. It will teach you efficient methods for saving, loading, and sharing your models across projects, facilitating seamless collaboration and reuse. The final section of the book covers advanced techniques for optimizing model accuracy and refining performance. You will be able to deploy your ML.NET models using Azure Functions and Web API, empowering you to integrate machine learning solutions seamlessly into real-world applications. WHAT WILL YOU LEARN ● Understand the basics of ML.NET and its capabilities in the machine learning landscape. ● Gain practical experience with the ML.NET Model Builder and command-line interface (CLI) to efficiently create models. ● Understand how to choose the most suitable algorithms and fine-tune them for optimal performance within ML.NET. ● Acquire knowledge on saving and loading ML.NET models, making them reusable and shareable across different projects. ● Delve into advanced strategies for enhancing the accuracy of your ML.NET models. ● Discover how to deploy ML.NET models using Azure Functions and Web API, enabling real-world application integration and scalability. WHO IS THIS BOOK FOR? This book is tailored for professionals and enthusiasts such as software developers, data scientists, and machine learning engineers who want to build and deploy machine learning models within the .NET ecosystem. IT professionals and technical leads overseeing machine learning projects in a .NET environment will also find this book valuable. Readers should have basic programming knowledge and a foundational understanding of machine learning concepts. TABLE OF CONTENTS 1. Introduction to ML.NET 2. Installing and Configuring ML.NET 3. ML.NET Model Builder and CLI 4. Collecting and Preparing Data for ML.NET 5. Machine Learning Tasks in ML.NET 6. Choosing and Tuning Machine Learning Algorithms in ML.NET 7. Inspecting and Interpreting ML.NET Models 8. Saving and Loading Models in ML.Net 9. Optimizing ML.NET Models for Accuracy 10. Deploying ML.NET Models with Azure Functions and Web API Index
Microsoft Azure Essentials Azure Machine Learning
Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.