Introduction to Machine Learning

author: John Quinn, Faculty of Computing and Informatics Technology, Makerere University
published: March 31, 2011,   recorded: February 2011,   views: 25124


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This talk gives an overview of machine learning from a practical perspective. Starting with examples of problems we might want to solve (in vision, signal processing, and geospatial inference), and the assumptions we have to make in order to get anywhere, it then covers a number of different supervised and unsupervised learning techniques. The talk concludes with ideas on how to evaluate a system, and when we should believe that a model is "right".

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Reviews and comments:

Comment1 Ozgur, June 17, 2011 at 1:42 p.m.:

The best web site addresses for computer science.
Texts, videos, graphics, questions about computer sciences.
Online computer science textbooks. Video audio lectures.

Comment2 karanja Evanson, February 10, 2014 at 6:20 p.m.:

Thats truly a cookbook approach John

Machine learning is great

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