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Applied Machine Learning (AML)

Schedule

DRPS Timetable

Week 1

 
Introduction to ML
Playlist  •  Slides  •  Handout
 
Introduction to Classification
Playlist  •  Slides  •  Handout
17 Sep
Q&A Session (16:10 @ 50 George Sq - G.03)
Slides

Week 2

 
Naive Bayes Classification
Playlist  •  Slides  •  Handout
 
Logistic Regression
Playlist  •  Slides  •  Handout
24 Sep
Q&A Session (16:10 @ 50 George Sq - G.03)
Slides
 
Lab 0 Introduction to Python and ML
Notebook  •  Solution

Week 3

 
Linear Regression
Playlist  •  Slides  •  Handout
 
Decision Trees
Playlist  •  Slides  •  Handout
01 Oct
Q&A Session (16:10 @ 50 George Sq - G.03)
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 @ 50 George Sq - G.03)
Slides
 
Tutorial 1 Classification and Naive Bayes
Problem Sheet  •  Solution

Week 5

 
Optimisation
Playlist  •  Slides  •  Handout
 
Generalisation
Playlist  •  Slides  •  Handout
15 Oct
Q&A Session (16:10 @ 50 George Sq - G.03)
Slides
 
Lab 2 Exploratory Data Analysis, Visualisation, and PCA
Notebook

Week 6

 
Evaluation
 
Model Selection
22 Oct
Q&A Session (16:10 @ 50 George Sq - G.03)
 
Tutorial 2 Optimization and Logistic Regression
Problem Sheet

Week 7

 
Clustering
 
Non-Linear Dimensionality Reduction
29 Oct
Q&A Session (16:10 @ 50 George Sq - G.03)
 
Lab 3 Evaluation
30 Oct
CW 1 Progress report due
01 Nov
CW 1 Progress feedback
 

Week 8

 
Recommender Systems
 
Neural Networks
05 Nov
Q&A Session (16:10 @ 50 George Sq - G.03)
 
Tutorial 3 Model Selection

Week 9

 
Ethics and Fairness
 
Further Topics
12 Nov
Q&A Session (16:10 @ 50 George Sq - G.03)
 
Lab 4 Neural Networks

Week 10

19 Nov
Q&A Session (16:10 @ 50 George Sq - G.03)
21 Nov
CW 1 Due
 
 
Tutorial 4 Ethics and Fairness