Schedule

DRPS Timetable

Week 1

Introduction to ML: Playlist • Slides • Handout

Introduction to Classification: Playlist • Slides • Handout

16 Sep

Q&A Session (16:10 @ AT - Lecture Theatre 4): Slides

Week 2

Naive Bayes Classification: Playlist • Slides • Handout

Logistic Regression: Playlist • Slides • Handout

23 Sep

Q&A Session (16:10 @ AT - Lecture Theatre 4): Slides

Lab 0 Introduction to Python and ML: Notebook • Solution

Week 3

Linear Regression: Playlist • Slides • Handout

Decision Trees: Playlist • Slides • Handout

30 Sep

Q&A Session (16:10 @ AT - Lecture Theatre 4): Slides

Lab 1 Classification, Naive Bayes, and Logistic Regression: Notebook • Solution

Week 4

Representing Data: Playlist • Slides • Handout

Exploratory Data Analysis: Playlist • Slides • Handout

CW 1 Start

08 Oct

Q&A Session (16:10 @ 40 AT - Lecture Theatre 5): Slides

Tutorial 1 Classification and Naive Bayes: Problem Sheet • Solution

Week 5

Optimisation: Playlist • Slides • Handout

Generalisation: Playlist • Slides • Handout

14 Oct

Q&A Session (16:10 @ 40 George Sq., Lecture Theatre A)

Lab 2 Exploratory Data Analysis, Visualisation, and PCA: Notebook

Week 6

Evaluation

Model Selection

21 Oct

Q&A Session (16:10 @ 40 George Sq., Lecture Theatre A)

Tutorial 2 Optimization and Logistic Regression: Problem Sheet

Week 7

Clustering

Non-Linear Dimensionality Reduction

28 Oct

Q&A Session (16:10 @ 40 George Sq., Lecture Theatre A)

Lab 3 Evaluation

29 Oct

CW 1 Progress report due

31 Oct

CW 1 Progress feedback

Week 8

Recommender Systems

Neural Networks

04 Nov

Q&A Session (16:10 @ 40 George Sq., Lecture Theatre A)

Tutorial 3 Model Selection

Week 9

Ethics and Fairness

Further Topics

11 Nov

Q&A Session (16:10 @ 40 George Sq., Lecture Theatre A)

Lab 4 Neural Networks

Week 10

18 Nov

Q&A Session (16:10 @ 40 George Sq., Lecture Theatre A)

20 Nov

CW 1 Due

Tutorial 4 Ethics and Fairness