February 2019
Intermediate to advanced
386 pages
9h 54m
English
Content preview from Hands-On Unsupervised Learning with Python
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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.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.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.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.
Why Python for data science and machine learning?
Before moving on with more technical discussions, I think it's helpful to explain the choice of Python as the programming language for this book. In the last decade, research in the field of data science and machine learning has seen exponential growth, with thousands of valuable papers and dozens of complete tools. In particular, thanks to its efficiency, elegance, and compactness, Python has been chosen by many researchers and programmers to create a complete scientific ecosystem that has been released for free.
Nowadays, packages such as scikit-learn, SciPy, NumPy, Matplotlib, pandas, and many others represent the backbone of hundreds of production-ready systems and their usage keeps growing. ...
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