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# Machine Learning: A Probabilistic Perspective

## (Adaptive Computation and Machine Learning)

by

**A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.**

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This ...more

Hardcover, 1104 pages

Published
August 24th 2012
by The MIT Press

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That being said, this is perhaps the best modern "reference" text on machine learning methods. If you are ...more

Surely it is not recommended for everyone, but at least recommended for those who want to understand deeply Machine Learning in a very comprehensive way.

There are many typos in the first 3 printings. The 4th (and later) is much better. What I bought (11/24/2017) is the 6th printing (the same as the 4th).

The book opens with a brief survey of the kinds of problems to which machine learning can be applied, and sketches the types of methods that can be used to model these problems.

After a short introduction to probability, the remaining 27 ...more

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