ML.NET Revealed:Simple Tools for Applying Machine Learning to Your Applications
Publisher Finelybook 出版社：Apress; 1st ed. edition (December 18, 2020)
pages 页数：192 pages
Get introduced to ML.NET, a new open source, cross-platform machine learning framework from Microsoft that is intended to democratize machine learning and enable as many developers as possible.
Dive in to learn how ML.NET is designed to encapsulate complex algorithms, making it easy to consume them in many application settings without having to think about the internal details. You will learn about the features that do the necessary “plumbing” that is required in a variety of machine learning problems, freeing up your time to focus on your applications. You will understand that while the infrastructure pieces may at first appear to be disconnected and haphazard, they are not.
Developers who are curious about trying machine learning, yet are shying away from it due to its perceived complexity, will benefit from this book. This introductory guide will help you make sense of it all and inspire you to try out scenarios and code samples that can be used in many real-world situations.
What You Will Learn
Create a machine learning model using only the C# language
Build confidence in your understanding of machine learning algorithms
Painlessly implement algorithms
Begin using the ML.NET library software
Recognize the many opportunities to utilize ML.NET to your advantage
Apply and reuse code samples from the book
Utilize the bonus algorithm selection quick references available online