February 2024
Intermediate to advanced
378 pages
10h 10m
English
Content preview from Data-Centric Machine Learning with Python
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Part 2: The Building Blocks of Data-Centric ML
In this part, we lay the groundwork for data-centric ML with four key principles that underpin this approach, giving you essential context before exploring specific techniques. Then we explore human-centric and non-technical approaches to data quality, examining how expert knowledge, trained labelers, and clear instructions can enhance your ML output.
This part has the following chapters:
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.