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@@ -85,6 +85,15 @@ <h2><a id="endorsements"></a>Endorsements</h2>
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where I’m fairly up to date with the literature. " --- <a href="https://web.engr.oregonstate.edu/~tgd/">Tom Dietterich</a>,
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Oregon State University
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<p>
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<li> "The prior version of Dr. Murphy's book was amongst the 3-4 books I recommended to students and machine learning colleagues
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at all levels as being essential to own, and, perhaps more importantly, to always have readily at hand.
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As machine learning has matured and evolved, no other comprehensive resource of this nature has even remotely
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kept pace with modern methodological developments. This new version is a blessing for the machine learning community and frankly,
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at this moment in time, is the only truly necessary machine learning book to own.
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Very few people in the world can do what Dr. Murphy has done here and the world owes him its thanks."
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-- <a href="https://www.cs.ubc.ca/~fwood/">Frank Wood</a>, UBC.
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<p>
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<li> "Whether teaching machine learning to undergrads, master students, or PhD students,
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I found myself time and time again choosing the 2012 "Machine Learning: A Probabilistic Perspective" as the primary textbook.

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