Lectures for COMP-598: Topics in Computer Science: Applied Machine Learning

Fall 2015


Some lecture notes will be linked to this web page, in PDF format. The reader for PDF files is available free from Adobe for UNIX, Apple Macintosh, and Windows.

Schedule

Lec.
Date
Topic
Lecture Material
Homeworks and Readings
1
Sep. 9

Introduction to machine learning.
Slides Read this paper.
Review basic notions of algebra and probabilities.
Suggested readings: Ch.1-2 of Bishop, Ch.1 of Hastie et al., Ch.2 of Shalev-Schwartz et al.
2
Sep.11

Linear regression.
Slides Suggested readings:
Ch.2 (Sec.2.1-2.4, 2.9) of Hastie et al.
Ch.3 of Bishop (Sec.3.1-3.2)
Ch.9 of Shalev-Schwartz
3
Sep. 16

Linear regression.
Slides
Mini-project #1 now available.
Suggested readings:
Ch.3 (Sec.3.1-3.4, 3.9) of Hastie et al.
Ch.3 of Bishop (Sec.3.1-3.2).
Ch.5 and 11 of Shalev-Schwartz
4
Sep. 18

Linear classification.
Slides Suggested readings:
Ch.4 of Hastie et al.
Ch.4 of Bishop (Sec.4.1-4.3).
Sec.9.3 of Shalev-Schwartz
5
Sep. 23

Linear classification (cont'd)
Slides Suggested readings:
Sec. 6.6.3 of Hastie et al.
Ch.4 of Bishop (Sec.4.1-4.3).
Sec.24.1-24.3 Shalev-Schwartz
A paper by Ng & Jordan (NIPS, 2001).
Ch.13 (Sec.13.1-13.4) of the book Introduction to Information Retrieval.
6
Sep. 25

Performance analysis and error estimation.
Slides
Suggested readings:
Ch.7 of Hastie et al.
Wagstaff (2012) paper
7
Sep. 30

Practical session with python and scikit-learn.
Slides
Notebook from the session
Mini-project #1 due.
8
Oct. 2

Decision trees
Slides
Mini-project #2 now available.
Suggested readings:
Sec.14.4 of Bishop.
Sec.9.2 of Hastie et al.
9
Oct. 7

Instance-based learning
Slides Suggested readings:
Sec.2.5 of Bishop.
Sec.13.3 of Hastie et al.
Ch.19 of Shalev-Schwartz
10
Oct. 9

Ensemble methods
Slides Suggested readings:
Sec.8.7, Ch.10 of Hastie et al.
Ch.14 of Bishop Ch.10 of Shalev-Schwartz
11
Oct. 14

Support vector machines
Slides Suggested readings:
Ch.7 of Bishop.
Ch.12 (Sec.12.1-12.4) of Hastie et al.
Ch.15 of Shalev-Schwartz
For more on convex optimization: see book by S. Boyd and L. Vandenberghe
12
Oct. 16

Support vector machines (cont'd)
Slides
13
Oct. 21

Feature construction and selection
Slides
Mini-project #2 due.
14
Oct. 23

Unsupervised learning
Slides
Mini-project #3 now available.
15
Oct. 28

Neural networks
Slides Suggested readings
Ch.11 of Hastie et al.
Ch.5 of Bishop
Ch.14 of Shalev-Schwartz
16
Oct. 30

Neural networks (cont'd)
Slides
17
Nov. 4

Deep learning
Slides
18
Nov. 6

Deep learning + Tutorial
Slides
Theano tutorial
19
Nov. 11

Problem solving session
Mini-project #3 due.
20
Nov. 13

Online / streaming data
Slides
Mini-project #4 now available.
21
Nov. 18

Parallelization for large-scale ML
Slides
22
Nov. 20

Midterm (confirmed).
23
Nov. 25

Semi-supervised learning
Slides
24
Nov. 27

Missing data.
Slides
25
Dec. 2

Final project presentation session
26
Dec. 4

Wrap-up
Slides
Final project report due Dec.11 (11:59pm) on CMT Track #4.