Found 1 comment on HN
tel · 2014-07-20 · Original thread
PRML is great. I haven't read PGM, but I took a relatively intensive course on it which had great lecture notes. Which I'd like to also suggest—lecture notes are often "skeletal books" which can bring you up to speed on a topic quickly given that you (a) are willing to work a bit more and (b) can fill in the missing fleshy bits with your own experience.

I'd also really like to suggest DGL ( and Bickel and Doksum ( These are two of my favorite core ML/stats books.

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