I recently finished reading Data Science from Scratch by Joel Grus. This book is a great introduction to data science concepts. It uses real code to demonstrate complex Python, data analytics, data science, and machine learning concepts.

I’m really glad I picked up this book as the first book I’ve read about machine learning. There was a great combination of mathematics, statistics, and real applications of machine learning algorithms.

The book starts out with a quick introduction to Python, followed by an in-depth review of all the math you need for the code to make sense.

If you’re looking for a book that’ll show you how to use Tensorflow or scikit-learn, this book is not for you. I’d recommend reading this book before diving into those. You’ll learn about the math behind popular machine learning libraries and implement basic versions of some of the most popular algorithms from scratch.

I think the next book I’ll pick up after this one is Python Data Science Handbook which will go into more detail on using a bunch of Python libraries to do some of this machine learning for me.

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