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Introduction to Machine Learning

This video was recorded at AI Bootcamp 2011 @ AITI-KACE, Accra, Ghana. 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".

Keywords:: videolectures, ocwc, oec

Disciplines:

Science and Technology / Computer Science / Programming & Programming Languages

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Material Type:: Presentation
Date Added to MERLOT:: February 8, 2015
Date Modified in MERLOT:: February 8, 2015
Author:: John Quinn, Faculty of Computing and Informatics Technology, Makerere University
Submitter:: The Open Education Consortium
Primary Audience:: College General Ed, College Lower Division, College Upper Division
Technical Format:: Video

Mobile Compatibility:: Not specified at this time
Language:: English
Cost Involved:: No
Source Code Available:: No
Creative Commons:: This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States