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murphyk authored Jul 29, 2022
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Expand Up @@ -85,6 +85,15 @@ <h2><a id="endorsements"></a>Endorsements</h2>
where I’m fairly up to date with the literature. " --- <a href="https://web.engr.oregonstate.edu/~tgd/">Tom Dietterich</a>,
Oregon State University

<p>
<li> "The prior version of Dr. Murphy's book was amongst the 3-4 books I recommended to students and machine learning colleagues
at all levels as being essential to own, and, perhaps more importantly, to always have readily at hand.
As machine learning has matured and evolved, no other comprehensive resource of this nature has even remotely
kept pace with modern methodological developments. This new version is a blessing for the machine learning community and frankly,
at this moment in time, is the only truly necessary machine learning book to own.
Very few people in the world can do what Dr. Murphy has done here and the world owes him its thanks."
-- <a href="https://www.cs.ubc.ca/~fwood/">Frank Wood</a>, UBC.

<p>
<li> "Whether teaching machine learning to undergrads, master students, or PhD students,
I found myself time and time again choosing the 2012 "Machine Learning: A Probabilistic Perspective" as the primary textbook.
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