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Machine Learning

Bayesian Reasoning and Machine Learning

  • 2015
  • 735 pages

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This practical introduction for final-year undergraduate and graduate students is ideally suited to computer scientists without a background in calculus and linear algebra. Numerous examples and exercises are provided.

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About the author

David Barber

David Barber received a BA in Mathematics from Cambridge University and subsequently a PhD in Theoretical Physics (Statistical Mechanics) from Edinburgh University. He is currently Reader in Information Processing in the Department of Computer Science UCL where he…

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