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Machine Learning

Anna University

Here are the best resources to pass Machine Learning. Find Machine Learning study guides, notes, assignments, and much more.

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ML-Lectures Notes-ReinforcementLearning

  • ML-Lectures Notes-ReinforcementLearning

  • Class notes • 70 pages • 2020
  •  To understand the concepts of Machine Learning.  To appreciate supervised learning and their applications.  To appreciate the concepts and algorithms of unsupervised learning.  To understand the theoretical and practical aspects of Probabilistic Graphical Models.  To appreciate the concepts and algorithms of advanced learning.
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ML-Lectures Notes--Sampling

  • ML-Lectures Notes--Sampling

  • Exam (elaborations) • 20 pages • 2020
  •  To understand the concepts of Machine Learning.  To appreciate supervised learning and their applications.  To appreciate the concepts and algorithms of unsupervised learning.  To understand the theoretical and practical aspects of Probabilistic Graphical Models.  To appreciate the concepts and algorithms of advanced learning.
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ML-Lectures Notes-COLT

  • ML-Lectures Notes-COLT

  • Exam (elaborations) • 61 pages • 2020
  •  To understand the concepts of Machine Learning.  To appreciate supervised learning and their applications.  To appreciate the concepts and algorithms of unsupervised learning.  To understand the theoretical and practical aspects of Probabilistic Graphical Models.  To appreciate the concepts and algorithms of advanced learning.
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