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Material Detail

A Course in Machine Learning

A Course in Machine Learning

A Course in Machine Learning is an introductory book that covers most major aspects of modern machine learning. Book Description Topics covered include:

Keywords:
neural networks, machine learning in practice, expectation maximization, algorithms, probabilistic modeling, the perceptron, linear models, unsupervised learning, structured learning and bayesian learning., beyond binary classification, Machine learning, decision trees, ensemble methods, graphical models, geometry and nearest neighbors, kernel methods, semi-supervised learning, learning theory, efficient learning, online learning
Disciplines:
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More about this material

Material Type:
Open (Access) Textbook
Date Added to MERLOT:
May 20, 2020
Date Modified in MERLOT:
May 20, 2020
Author:
Submitter:
Rama Komaragiri
Primary Audience:
College Upper Division, Graduate School, Professional
Technical Format:
PDF, Website
Mobile Compatibility:
Not specified at this time
Technical Requirements:
A PDF reader
Language:
English
Cost Involved:
No
Source Code Available:
Yes
Creative Commons:
No

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