Machine Learning

Machine Learning

This course covers a broad understanding of the field of machine learning and statistical pattern recognition. Topics include classification and linear regression, Bayesian network, decision trees, SVMs, statistical learning method, unsupervised learning and reinforcement learning.

Course Objectives

At the end of the course, participants are able to:

1. Explain the concepts and techniques for supervised learning, semi-supervised learning and unsupervised learning.
2. Use the appropriate machine learning techniques for given sample datasets.
3. Apply practical solutions to solve common problems in machine learning.

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