Create, train, evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET Core Key Features * Get well-versed with ML.NET framework, components, and APIs using practical examples * Learn how to build, train, and evaluate popular machine learning algorithms with ML.NET offerings * Extend your existing machine learning models by integrating with TensorFlow and other libraries Book Description In today's world, machine learning (ML) is widely used in many industries such as science, healthcare, research, etc. For all the .NET enthusiasts, in March 2018 Microsoft has introduced the ML.NET to work with ML. With this book, you will explore various ML models available to develop using C# code for building ML.NET applications. The book starts with giving an overview of ML and the types of ML algorithms used. It talks in deep about what is ML.NET and why we need it to build ML applications. You will understand the ML.NET framework, its components, and APIs. The book will serve as a practical guide to help you understand how to build smart applications using ML.NET library. You will be well versed in how to implement ML algorithms such as regression, classification, and clustering algorithms with real-world examples and datasets. Each chapter will cover a practical implementation showing how to implement ML within .NET applications. You will also learn about integrating TensorFlow in ML.NET application. Later you will also learn to store the regression model housing price prediction result to the database and display the real-time predicted results from the database to your web application using ASP.NET Core Blazor and SignalR. By the end of this book, you will be able to perform basic to advance level ML tasks in ML.NET. What you will learn * Understand ML.NET framework, components, and APIs using C# code * Create and work in ML.NET for regression models for housing price prediction * Train and evaluate classification models for sentiment prediction of your website comments * Work with clustering models for customer segmentation of your product for sales * Understand how to work with Entity Framework (EF) and Web API in ASP.NET Core Blazor * Display the real-time saved predicted results in your web application using ASP.NET Core Blazor and SignalR * Learn to integrate TensorFlow in ML.NET application Who This Book Is For If you are a .NET developer and want to implement machine learning models using ML.NET, this is the book you need. This book will also be beneficial for data scientists, machine learning developers who are looking for effective tools to implement various machine learning algorithms. Prior knowledge and a basic understanding of C# or .NET is mandatory to proceed with this book.

Book Information
ISBN 9781789801781
Author Jarred Capellman
Format Paperback
Page Count 298
Imprint Packt Publishing Limited
Publisher Packt Publishing Limited
Weight(grams) 191g