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I am almost finished reading ESL; Elements of Statistical Learning. I come from a strong mathematical and statistical background, and that was my first book about Machine Learning.

What other books would be good to go over now?

I am aware of books such as:

  • Machine Learning: A Bayesian and Optimization Perspective (.Net Developers Series)
  • Pattern Recognition and Machine Learning by Bishop
  • Machine Learning: A Probabilistic Perspective, by Murphy

and I have heard they are all good. However I am unsure of the order of reading or if you may; 'double-reading' same stuff (although that would not be a terrible idea as not everything stuck with me from ESL).

Thank you

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    $\begingroup$ Bishop's book is good. It is also better preparation for the Bayesian skew in the ML field, which you won't have gotten from ESL. $\endgroup$ Apr 23, 2020 at 11:26

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You're going in the right way! In my journey towards machine learning, I found Python Machine Learning by Sebastian Raschka very helpful for the start. Though I read a lot books then, this one seriously helped me to kick start the journey.

Beside this one, you could check out some more books. Here is a good list I followed. Happy Machine Learning.

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