Book Review: Python Machine Learning – Third Edition by Sebastian Raschka, Vahid Mirjalili | Book Review - insideBIGDATA

Take a look at Daniel D. Gutierrez's, Managing Editor and Resident Data Scientist for insideBIGDATA, Book Review: Python Machine Learning below.

Python Machine Learning:
Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition

I had been looking for a good book to recommend to my “Introduction to Data Science” classes at UCLA as a text to use once my class completes … sort of the next step after learning the basics. That’s why I was looking forward to reviewing the new 3rd edition of the widely acclaimed title “Python Machine Learning” by Sebastian Raschka, Vahid Mirjalili. The book is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a useful resource you’ll keep coming back to as you fill up your data science toolbox.

I knew I was going to like it the minute I started thumbing through the pages and saw some mathematics. I had been warning my students early on that eventually they’d have to break down and engage the mathematical foundations of machine learning to become a down-in-the-trenches data scientist, so this book fits that bill nicely. Many of the chapters start off with some theoretical aspects of the topic being discussed, including some math, followed by plenty of nicely written Python code. It should be noted that this book is not for beginners, and if you don’t know the Python language, you’ll have to find another learning resource before consuming this book...

I highly recommend this book for any advancing data scientist who needs a completely state-of-the-technology picture of our field. I’ve carefully been going through the book myself as a refresher course for the theory, math and code related to machine learning.
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Source: insideBIGDATA