Ultimate Machine Learning With Ml Net
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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
Introducing Machine Learning
Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning. · 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you · Explore what’s known about how humans learn and how intelligent software is built · Discover which problems machine learning can address · Understand the machine learning pipeline: the steps leading to a deliverable model · Use AutoML to automatically select the best pipeline for any problem and dataset · Master ML.NET, implement its pipeline, and apply its tasks and algorithms · Explore the mathematical foundations of machine learning · Make predictions, improve decision-making, and apply probabilistic methods · Group data via classification and clustering · Learn the fundamentals of deep learning, including neural network design · Leverage AI cloud services to build better real-world solutions faster About This Book · For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills · Includes examples of machine learning coding scenarios built using the ML.NET library