1. Statistical pattern recognition and machine learning Jen-Chang Liu, Spring, 2008

2. Class goal Techniques for advanced machine perception Familiar with probabilistic methods (probability distributions, estimations, Bayesian inference, graphical model) Basic pattern recognition methods (dimension reduction, PCA, clustering … )

3. Textbook Pattern Recognition and Machine Learning, Chris Bishop Pattern Recognition and Machine Learning Reference: Introduction to machine learning, Ethem Alpaydin Introduction to machine learning

4. Resources Course websites CMU, machine learning, Carlos Guestrin CMU, machine learning CMU, Advanced Machine Perception, Alexei (Alyosha) Efros CMU, Advanced Machine PerceptionAlexei (Alyosha) Efros NCNU moodle (moodle.ncnu.edu.tw)

5. Grading Students are expected to: attend the lectures, and participate in class discussions present one or a cluster of research papers do several projects