Found 2 comments on HN
shogunmike · 2015-05-12 · Original thread
Some good books on Machine Learning:

Machine Learning: The Art and Science of Algorithms that Make Sense of Data (Flach):

Machine Learning: A Probabilistic Perspective (Murphy):

Pattern Recognition and Machine Learning (Bishop):

There are some great resources/books for Bayesian statistics and graphical models. I've listed them in (approximate) order of increasing difficulty/mathematical complexity:

Think Bayes (Downey):

Bayesian Methods for Hackers (Davidson-Pilon et al):

Doing Bayesian Data Analysis (Kruschke), aka "the puppy book":

Bayesian Data Analysis (Gellman):

Bayesian Reasoning and Machine Learning (Barber):

Probabilistic Graphical Models (Koller et al):

If you want a more mathematical/statistical take on Machine Learning, then the two books by Hastie/Tibshirani et al are definitely worth a read (plus, they're free to download from the authors' websites!):

Introduction to Statistical Learning:

The Elements of Statistical Learning:

Obviously there is the whole field of "deep learning" as well! A good place to start is with:

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