A Course in Machine Learning (Hal Daume III)

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A Course in Machine Learning (Hal Daume III)

The majority of the key facets of contemporary machine learning are covered in this collection of basic materials (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.). Its main emphasis is on broad applications with a solid foundation. An undergraduate course can use a portion of the content; a graduate course could likely cover the entire thing plus more.

Ebook Details

About the Authors
Associate professor of computer science and linguistics at the University of Maryland is Hal Daume III.
Published Date / Year
(January 2017)
eBook Format
PDF Files and a Single PDF (227 Pages)

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