January 2025
Intermediate to advanced
436 pages
11h 10m
English
Content preview from Feature Engineering for Modern Machine Learning with Scikit-LearnBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 1: Real-World Data Analysis Projects
In this chapter, we embark on a practical journey through data analysis, immersing ourselves in real-world projects that bridge the gap between theoretical concepts and tangible applications. Our exploration will encompass a comprehensive approach to working with real-world datasets, covering the entire spectrum from initial data collection and meticulous cleaning processes to sophisticated analysis techniques and compelling visualizations.
The projects we'll delve into span across diverse domains, each presenting its own set of unique challenges and opportunities for insight. This variety provides an invaluable platform to apply and refine our analytical techniques in a wide range of contexts, enhancing ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
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.