English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 0h 38m | 99 MB
If you’re looking to get into the world of machine learning models, but don’t know where to start, ML.NET is free software machine learning library for C# that allows you to build models without having to know all the theory behind machine learning. In this course, Jonathan Wood introduces you to ML.NET and shows how you can use it to leverage machine learning within your .NET applications. Jonathan starts with the basics of machine learning and covers both what it’s good for and scenarios when it’s not the best option. He then gets into the tools that you can utilize to help you get started building machine learning models. By the end of this course, you’ll have a better idea of the benefits of using ML.NET and why it’s a great tool for C# developers who are interested in machine learning.
Table of Contents
Introduction
1 Get started with ML.NET
2 What you should know
1. Machine Learning and ML.NET
3 What is machine learning
4 What machine learning isn’t
5 Current state of machine learning
6 What is ML.NET
7 Why use ML.NET
8 Using ML.NET in Visual Studio
2. Introduction to the ML.NET API and Tools
9 Introducing the ML context
10 High-level look at the ML.NET API
11 Using the ML.NET CLI
12 Using the ML.NET model builder
13 Building models with AutoML
14 Challenge Use the ML.NET API and tools to build a model
15 Solution Use ML.NET API and tools to build a model
Conclusion
16 Next steps
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