April 2018
Beginner to intermediate
282 pages
6h 52m
English
Content preview from Hands-On Automated Machine Learning
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What this book covers
Chapter 1, Introduction to AutoML, creates a foundation for you to dive into AutoML. We also introduce you to various AutoML libraries.
Chapter 2, Introduction to Machine Learning Using Python, introduces some machine learning concepts so that you can follow the AutoML approaches easily.
Chapter 3, Data Preprocessing, provides an in-depth understanding of different data preprocessing methods, what can be automated, and how to automate it. Feature tools and auto-sklearn preprocessing methods will be introduced here.
Chapter 4, Automated Algorithm Selection, provides guidance on which algorithm works best on which kind of dataset. We learn about the computational complexity and scalability of different algorithms, along ...
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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.