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ภาคพิเศษ: Machine Learning and Neural Network (2/2016)Lecturer: Jakramate Bootkrajang Office : 17.00-18.00 Tuesday,Friday @ CSB 107 Email: jakramate.b@cmu.ac.th |
- Welcome to course's homepage.
- I. Introduction
- Introduction -[slides]
- Maths refresher -[slides]
- Introduction to Julia programming - [slides]
- II. Linear machines
- Bayes classifiers and Linear Discriminant - [slides] [handout]
- Logistic Regression - [slides] [handout]
- III. Non-linear machines
- Support Vector Machine and Kernel Method [slides] [handout]
- Ensemble method [slides] [handout] [AdaBoost Derivation] animation
- IV. Lab
- 1. Julia Intro - [slides]
- 2. Julia Reborn - [slides]
- 3. Julia Finale - [slides]
- Banana dataset -[download]
- Boston dataset -[download]
- Wine dataset -[download]
- Sentiment data -[positive] [negative]
Assignments
Useful resources
- Books
- Pattern Classification: Peter E. Hart, David G. Stork, and Richard O. Duda, WILEY.
- Kernel Methods for Pattern Analysis: John Shawe-Taylor and Nello Cristianini, CAMBRIDGE PRESS.
- Julia programming
- Julia Manual
- Julia for Quantitative Economics
- Julia by Examples
- Similar courses at other universities
- Penn State's STAT557 by Prof. Jia Li link
- University of Washington's CSS490 by Prof. Jeffry Howbert link