February 2020
Beginner to intermediate
400 pages
11h 54m
English
Content preview from Introducing Machine Learning
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Contents at a Glance
PART I LAYING THE GROUNDWORK OF MACHINE LEARNING
CHAPTER 2 Intelligent Software
CHAPTER 3 Mapping Problems and Algorithms
CHAPTER 4 General Steps for a Machine Learning Solution
PART II MACHINE LEARNING IN .NET
CHAPTER 7 Implementing the ML.NET Pipeline
CHAPTER 8 ML.NET Tasks and Algorithms
PART III FUNDAMENTALS OF SHALLOW LEARNING
CHAPTER 9 Math Foundations of Machine Learning
CHAPTER 10 Metrics of Machine Learning
CHAPTER 11 How to Make Simple Predictions: Linear Regression
CHAPTER 12 How to Make Complex Predictions and Decisions: Trees
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.