Machine Learning Basics
Machine Learning Basics
Cong Li
Course in Childen's Computer Center, Children's Palace of Chinese Welfare Institute
Fall 2017 and Spring 2018; Spring and Fall 2015; Fall 2012 and Spring 2013; Fall 2010 and Spring 2011; Fall 2008 and Spring 2009; Fall 2006 and Spring 2007; Fall 2003 and Spring 2004
Course Description
Machine learning studies how computer programs improve their performances through experiences. This course provides a brief introduction to machine learning. The topics include the major supervised learning approaches, recent directions in machine learning, and how these methods are applied to solve problems.
Lecture Notes
1. General Introduction (2.5 lessons)
2. Typical Classifiers (10 lessons)
3. Ensemble Learning (3.5 lessons)
4. Leveraging Unlabeled Data (2.5 lessons)
5. Learning Markov Models (4 lessons)
6. Reinforcement Learning (4 lessons)
Class Assignments
1. Build a Naive Bayesian Classifier
2. Ensemble of Naive Bayesian Classifiers
3. Active Learning with Selective Sampling
Popular Science Talk
A Cross-Section View of Machine Learning