Schedule
| Week | Lecture | Lab | Workshop | |
|---|---|---|---|---|
| 1 | Introduction to ML
Introduction to Classification | Q&A Session Wednesday 6.15pm Collaborate | ||
| 2 | Naive Bayes Classification
Logistic Regression | LAB 0 Introduction to Python and ML | Q&A Session Wednesday 6.15pm Collaborate | |
| 3 | Linear Regression
Decision Trees | LAB 1 Classification, Naive Bayes, and Logistic Regression Notebook • Solution see Learn 'Lab' folder Tuesday 6-7pm GMT Collaborate Thursday 6-7pm on Zoom see email or Piazza for details | Q&A Session Wednesday 6.15pm Zoom
| |
| 4 | Representing Data
Exploratory Data Analysis | TUTORIAL 1 Classification and Naive Bayes Problem Sheet • Solution Monday at 10-11am on Zoom Thursday at 5-6pm on Zoom | Q&A Session Wednesday 6.15pm Zoom
| |
| 5 | Optimisation
Generalisation
CW 1 Start Monday | LAB 2 Exploratory Data Analysis, Visualisation, and PCA Notebook • Solution Tuesday and Thursday 6-7pm GMT Zoom | Q&A Session Wednesday 6.15pm Zoom | |
| FLW | Flexible Learning Week 16-20th Feb | |||
| 6 | Evaluation
Model Selection | TUTORIAL 2 Optimization and Logistic Regression Problem Sheet • Solution | Q&A Session 6.15pm Zoom
| |
| 7 | Clustering
Non-Linear Dimensionality Reduction
CW 1 Due Monday | LAB 3 Evaluation Notebook • Solution Tuesday and Thursday 6-7pm GMT Zoom
| Q&A Session 6.15pm Zoom | |
| 8 | Recommender Systems
Neural Networks | TUTORIAL 3 Model Selection Problem Sheet • Solution | Q&A Session 6.15pm Zoom | |
| 9 | Ethics and Fairness
Further Topics | LAB 4 Neural Networks Notebook • Solution Tuesday and Thursday 6-7pm GMT Zoom | Q&A Session 6.15pm Zoom | |
| 10 |
Monday: Mini-Project Start due 20/4/26 at the beginning of Revision Week
| TUTORIAL 4 Ethics and Fairness Problem Sheet • Solution | Q&A Session 6.15pm Zoom |