Lectures

Lecturers Christoph Haase
Varun Kanade
Hours Mondays and Wednesdays 16h-17h; Fridays 10h-11h
Location Lecture Theatre A (CS Building)

Note 1. Lecture notes may not be posted for every lecture, but only if the material covered deviates significantly from that found in the recommended textbooks. They should not be used as a substitute for actually reading the textbooks.

Note 2. Students wishing to look through the lecture notes and slides ahead of time may consult last year's version here. However, please note that slides and lecture notes may change and please make use of this year's version when revising.

Note 3. Code used in the lecture slides is available here. You are encouraged to play with the code, both to improve your understanding of the material taught in the lectures as well as preparing you for the practicals.

Note 4. You may find that you struggle with parts of suggested reading or that they are not directly related to what we covered in the lecture. We suggest you skip these sections and return to them once you've understood the material covered in the lecture and want to increase your understanding further.


Lecture Schedule

Date Topic Handouts Reading Venue

9/10/2017 Introduction to Machine Learning [slides]
[notes]
[code]

(Mur) Chap. 1
(GBC) Chap. 5.1
Lecture Theatre A
Computer Science
11/10/2017 Mathematical Basics [slides]



(GBC) Chap. 2,3
(Mur) Chap. 2

Lecture Theatre
Museum of Natural History
13/10/2017 Linear Regression [slides]
[notes]
[code]

(GBC) Chap. 5.1.4
[wiki page]

Lecture Theatre L1
Mathematics Insitute
16/10/2017 Maximum Likelihood [slides]
[notes]
[code]

(Mur) Chap. 7.1-4
(GBC) Chap. 5.5

Lecture Theatre
Museum of Natural History
18/10/2017 Basis Expansion, Learning Curves, Overfitting [slides]
[notes]
(Mur) Chap. 7.5
(GBC) Chap. 5.2-4


Lecture Theatre
Museum of Natural History
20/10/2017 Regularization, Validation, Model Selection [slides]
[notes]
(Mur) Chap. 7.5
(GBC) Chap. 5.2-4


Lecture Theatre A
Computer Science
23/10/2017 Bayesian Approach to Machine Learning

[slides]
[notes]
(Mur) Chap. 7.6
(GBC) Chap. 5.6


Lecture Theatre
Museum of Natural History
25/10/2017 Optimization I [slides]
[notes]
(Mur) Chap. 8.3, 8.5, 13.1, 13.3-4
(GBC) Chap. 8

Lecture Theatre
Museum of Natural History
27/10/2017 Optimization II [slides]
[notes]
(Mur) Chap. 8.3, 8.5, 13.1, 13.3-4
(GBC) Chap. 8

Lecture Theatre
Medical Sciences Teaching Centre
30/10/2017 Generative Models [slides]
[notes]
[code]

(Mur) Chap. 3.5, 4.1-2

Lecture Theatre
Museum of Natural History

01/11/2017 Logistic Regression [slides]
[notes]
[code]

(Mur) Chap. 8.1-3, 8.6
Notes on basic Information Theory

Lecture Theatre
Medical Sciences Teaching Centre

03/11/2017 Support Vector Machines (SVM) [slides]
[notes]
(Mur) Chap. 14.5

Lecture Theatre A
Computer Science

06/11/2017 Kernel SVMs [slides]
[notes]
(Mur) Chap. 14.1-2

Lecture Theatre
Medical Sciences Teaching Centre

08/11/2017 Neural Networks [slides]
[notes]
[code]

(Nie) Chap. 1, 2
(GBC) Chap. 6
Lecture Theatre A
Computer Science

13/11/2017 Neural Networks [slides]
[notes]
[code]

(Nie) Chap. 5, 6
(GBC) Chap. 7, 9
Lecture Theatre A
Computer Science

15/11/2017 Neural Networks [slides]
[notes]
[code]

(Nie) Chap. 5, 6
(GBC) Chap. 7, 9
Lecture Theatre A
Computer Science

20/11/2017 Principal Component Analysis (PCA)

[slides]
[notes]
(Mur) Chap. 12.2
Lecture Theatre A
Computer Science

22/11/2017 Kernel PCA [slides]
[notes]
(Mur) Chap. 12.3, Chap. 14.4.4
Lecture Theatre A
Computer Science

27/11/2017 Clustering [slides]
[notes]
[code]

(Mur) Chap. 11.4.2.5, Chap. 25.1, 25.3, 25.5
Lecture Theatre A
Computer Science

29/11/2017 Spectral Clustering
&
Summary
[slides]
[notes]
[code]
[slides]
(Mur) Chap. 25.4
Lecture Theatre A
Computer Science