Course: Introduction to Pattern Recognition

Instructor: Prof. Yen-Yu Lin

Introduction

An introduction to pattern recognition

Office Hours

Wednesday 1:30 pm ~ 3:30 pm at EC118

Please contact instructor Yen-Yu Lin at [email protected] or TA Jimmy Yang at [email protected], TA Chung-Hsuan Cheng at [email protected]

Grading Policy

• 4 homework assignments: 40%, see HW READEME
• Midtern exam: 30%
• Final exam: 30%

Syllabus

Week	Date	Topic	Remarks
1	03/04, 03/06	Introduction
2	03/11, 03/13	Linear Model for Regression
3	03/18, 03/20	Linear Model for Classification	HW1 anoounce
4	03/25, 03/27	Neural Networks
5	04/01, 04/03	Dimensionality Reduction	HW1 due
6	04/08, 04/10	Kernel Method I
7	04/15, 04/17	Kernel Method II	HW2 announce
8	04/22, 04/24	Ensemble Method I
9	04/29, 05/01	Midtern Exam	W2 due
10	05/06, 05/08	Ensemble Method II	HW3 announce
11	05/13, 05/15	Clustering
12	05/20, 05/22	Neural Networks and Deep Learning	HW3 due, HW4 announce
13	05/27, 05/29	Convolutional Neural Networks (CNN)
14	06/03, 06/05	Representative CNN Models	HW4 due
15	06/10, 06/12	Deep Autoencoder (DAE) and Generative Adversarial Networks (GAN)
16	06/17, 06/19	Final exam
17	06/24, 06/26	Guest lecture