Hsuan-Tien Lin > Courses > Machine Learning, Fall 2012

Hsuan-Tien Lin

Home | MOOCs | AIsk | Courses | Research Group | Awards | Publications | Presentations | Programs/Data

Machine Learning, Fall 2012

Course Description

Machine learning allows computational systems to adaptively improve their performance with experience accumulated from the data observed. This course introduces the basics of learning theories, the design and analysis of learning algorithms, and some applications of machine learning.

People

instructor: Hsuan-Tien Lin (htlin AT csie . ntu . edu . tw) [office hour: Thursdays 14:30-15:30, CSIE R314 or by appointment]
TAs: Wei-Yuan Shen, Ya-Hsuan Chang, Ching-Pei Lee, Han-Jay Yang, Chun-Heng Huang (ml2012ta AT csie . ntu . edu . tw) [TA hour: Tuesdays 17:30-18:30, CSIE R106; Wednesdays 17:30-18:30, CSIE R110]

Course Information

Time: Mondays 1:20pm to 3:10pm; Thursdays 1:20pm to 2:10pm
Room: Freshman (Shing-Shen) Building, R303
Textbook: Learning from Data, by Yaser Abu-Mostafa, Malik Magdon-Ismail and Hsuan-Tien Lin
Language: English
Grading: 70% homework, 30% project (tentative)
Full Course Website: http://ceiba.ntu.edu.tw/1011ML

Announcements

homework 7 announced on 12/13/2012, due 12/27/2012
homework 6.5 announced on 12/4/2012, due 12/10/2012 before the class
homework 6 announced on 11/29/2012, due 12/13/2012
final project announced on 11/21/2012, report due 01/14/2013
homework 5 announced on 11/16/2012, due 11/29/2012
homework 4 extended to 11/16/2012 because of NTU Birthday
homework 4 announced on 10/28/2012, due 11/15/2012
homework 3 announced on 10/11/2012, due 10/25/2012
homework 2.2 clarified (polished) on 10/6/2012
homework 2 announced on 9/27/2012, due 10/11/2012
homework e/2 announced on 9/24/2012, no due date
homework guideline announced on 9/19/2012
homework 1 announced on 9/13/2012, due 9/27/2012
homework 0.5 announced on 9/10/2012, due 9/13/2012 before the class
policy slightly updated on 9/10/2012 (about the gold medal part), and explained in class
We will change the classroom to Freshman (Shing-Shen) Building, R303 starting 9/10/2012!!
homework 0 announced on 8/15/2012, self-graded, be sure to study those before the class
policy announced on 8/15/2012

Class Policy

main policy: here
a reminder that you must write your homework in English
For the late homework submissions, students should contact any of the TAs for the exact submission procedure and write down the submission time on the late parts clearly.

Course Plan (tentative)

date	syllabus	todo/done	suggested reading
9/10,13	introduction	policy explained in class; homework 0.5 announced; homework 1 announced	LFD Sections 1.0, 1.1
9/17,20	introduction	pros explained in class	LFD Sections 1.2, 1.3 (until p.22)
9/24,27	introduction/generalization	homework 1 due; homework e/2 announced; homework 2 announced	LFD Sections 1.3, 2.0, 2.1 (until p.45)
10/1,4	generalization		LFD Sections 2.1, 1.4
10/8,11	generalization/linear model	homework 2 due; homework 3 announced	LFD Sections 2.2, 3.0, 3.1, 3.2 (until p.85)
10/15,18	linear model		LFD Sections 3.2, 3.3
10/22,25	linear model/overfitting	homework 3 due; homework 4 announced	LFD Sections 3.4, 4.0, 4.1
10/29,11/1	regularization/validation		LFD Sections 4.2, 4.3 (until p.145)
11/5,8	validation/principles	good luck with your other midterms	LFD Sections 4.3, 5.0, 5.1, 5.2, 5.3
11/12,15	support vector machine	no class on 11/15 because of NTU Birthday; homework 4 due; homework 5 announced	Draft Sections 8.1, 8.4
11/19,22	support vector machine	final project announced	Draft Sections 8.2
11/26,29	support vector machine	homework 5 due; homework 6 announced	Draft Sections 8.2, 8.3
12/3,6	neural network/data mining	class on 12/3 is TA session; no class on 12/6, because of NIPS conference; homework 6.5 announced	Useful Info about Final Project; Draft Sections 7.1, 7.2
12/10,13	aggregation	homework 6 due; homework 7 announced	Draft Slide Chapter 10 (until p.19)
12/17,20	aggregation		Draft Slide Chapter 10
12/24,27	similarity-based models	homework 7 due	Draft Chatper 6 (kNN, RBF Network, kMeans)
12/31,1/3	no class on 12/31; unsupervised, semi-supervised, active learning		class notes
1/7	summary, award ceremony	final project due	class notes

Last updated at CST 13:07, October 04, 2023
Please feel free to contact me: htlin.email.png