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I have Deep Learning with Python (Chollet, first edition) and Hands-On Machine Learning (Géron, first edition). Both books are highly recommended. Introduction
by auraham 6y ago
I have Deep Learning with Python (Chollet, first edition) and Hands-On Machine Learning (Géron, first edition). Both books are highly recommended.
Introduction to Statistical Learning is also available for free online:
http://faculty.marshall.usc.edu/gareth-james/ISL/ http://faculty.marshall.usc.edu/gareth-james/ISL/
Although I only read a few chapters from that book, I really like it (but I would have preferred a python version of the book).
Personally, if you have to pick three books from the list, ypu can start with these three options.
- alanfranz 6y agoYou can find a couple of repos (google them) that show the exercises in Python, I had written a post on my own blog some time ago: https://www.franzoni.eu/machine-learning-a-sound-primer/ https://www.franzoni.eu/machine-learning-a-sound-primer/
- auraham 6y agoGood to know, thanks for the link!
- yboris 6y agoI wholeheartedly second "Deep Learning with Python" by François Chollet! It's an excellent 'zero-to-hero' text for understanding deep neural networks, some common architectures, and the code (and theory) to get them to work. One thing missing is how to prepare data for deep learning -- but that's just standard ETL you learn elsewhere.
- auraham 6y agoYou can check Géron's book to know more about data preparation, specifically the second chapter. This chapter details an end-to-end machine learning project (price prediction). Here, the author describes scikit learn's pipelines for automating preprocessing tasks for your dataset.