Course details of CS 419 - Introducing to Machine Learning

Course Name Introducing to Machine Learning
Total Credits 6
Type T
Lecture 2
Tutorial 0
Practical 1
Selfstudy 0
Half Semester N
Prerequisite CS 213
Text Reference Tom Mitchell, Machine Learning. McGraw-Hill, 1997.     Pattern recognition and machine learning by Christopher Bishop, SPringer Verlag 2006     Selected papers
Description This course will provide a broad overview of Machine Learning with a stress on applications. Supervised learning: Decision trees, Nearest neighbor classifiers, Generative classifiers like naive Bayes, Support vector Machines Unsupervised learning: K-Means clustering, Hierarchical clustering, EM, Itemset mining Applications: image recognition, speech recognition, text and web data retrieval, bio-informatics, commercial data mining.
Last Update 21-07-2011 10:42:37.312685