Tentative schedule for COMP 451

Lec. Date Topic Reading Additional Info
1
Jan. 7
Introduction to machine learning		 Lecture notes (Chap 1)
Jamboard
Mandatory reading: This paper.

Part I: Decision Boundaries
2
Jan. 12
Instance-based learning		 Lecture notes (Chap 2)
Jamboard
3
Jan. 14
Parametric Learning and Perceptrons (Part I)		 Lecture notes (Chap 3; Sec 3.1-3.2)
Jamboard
4
Jan. 19
Parametric Learning and Perceptrons (Part II)		 Lecture notes (Chap 3; Sec 3.3)
Jamboard

Part II: Likelihood
5
Jan. 21
Maximum Likelihood		 Lecture notes (Chap 4)
Jamboard
6
Jan. 26
Naive Bayes (Part I)		 Lecture notes (Chap 5; Sec 5.1-5.3)
Jamboard
7
Jan. 28
Naive Bayes (Part II)		 Lecture notes (Chap 5; Sec 5.3-5.5)
Jamboard
 Theory Assignment 1 Released
Practice Assignment 1
Practice Assignment 1 (with solutions)
Assignment 1 [Theory Assignment 1] (due Feb 9th)
8
Feb. 2
Logistic Regression		 Lecture notes (Chapter 6)
Jamboard

Part III: Optimization
9
Feb. 4
Empirical Risk Minimization		 Lecture notes (Chapter 7)
Jamboard
10
Feb. 9
Gradient Descent and Convexity		 Lecture notes (Chapter 8)
Jamboard
 Theory Assignment 1 Due
11
Feb. 11
Linear Regression		 Lecture notes (Chapter 9)
Jamboard
 Assignment 2 [Practical Assignment 1] (due Feb 23rd)
12
Feb. 16
Generalization and Overfitting		 Lecture notes (Chapter 10)
Jamboard
13
Feb. 18
Regularization		 Lecture notes (Chapter 11)
Jamboard

Part IV: Information
14
Feb. 23
Information Theory		 Lecture notes (Chapter 12)
Jamboard 		Assignment 2 / Practical Assignment 1 Due
Theory Assignment 2 (Practice)
Theory Assignment 2 (Practice with Solutions)
Assignment 3 [Theory Assignment 2] (due March 11)
15
Feb. 25
Decision Trees		 Lecture notes (Chapter 13)
Jamboard
March 2

Study Break
March 4

Study Break

Part V: Latent Variables
16
March 9

Clustering		 Lecture notes (Chapter 14)
Jamboard
17
March 11

Mixture Models		 Lecture notes (Chapter 15)
Jamboard 		Assignment 3 [Theory Assignment 2] Due
Assignment 4 [Practical Assignment 2] (due March 23rd)

Part VI: Representations
18
March 16

Feature Design		 Lecture notes (Chapter 16)
Jamboard
19
March 18

PCA		 Lecture notes (Chapter 17)
Jamboard
20
March 23

Boltzmann Machines		 Lecture notes (Chapter 18)
Jamboard 		Practical Assignment 2 Due

Part VII: Neural Networks
21
March 25

Feedforward Neural Networks		 Slides
 Theory Assignment 3 (Practice)
Theory Assignment 3 (Practice with Solutions)
Assignment 5 [Theory Assignment 3] (due April 6)
22
March 30

Optimizing Neural Networks		 Slides
23
April 1

Convolutional Neural Networks		 Slides
24
April 6

Recurrent Neural Networks		 Slides
 Theory Assignment 3 Due
25
April 8

Autoencoders		 Slides
26
April 13

Review