IAML-PG2: Schedule

Schedule

WeekTopicsLabSmall group tutorialCoursework     
 		Class meeting (Wednesday)     
 
0Probability Topics    

1

 

Thinking About DataLab 0: Introduction to Python and ML packages  (i) Course overview and activities, overall plan. Q&A on Labs, Assignments and Coursework     
(ii) Thinking about data Q&A     
(iii) Probability Q&A

2

 

Naive Bayes

Decision Trees

Lab 1: Data Analysis and Visualisation and Multinomial Naive Bayes  (i): Bayes rule Q&A     
(ii): Naive Bayes Q&A      
(iii): Decision Trees Q&A

3

 

Generation

Evaluation

 Tutorial 1: Naive Bayes and Feature Engineering (i): Generalisation and Evaluation Q&A

4

 

Linear Regression

Logistic Regression

Lab 2: Decision Trees and Linear Regression  (i): Linear Regression Q&A     
(ii): Logistic Regression Q&A

5

 

Optimisation

Regularization

 Tutorial 2: Decision Trees and Gaussian Naive Bayes  (i): Optimisation and Regularisation Q&A

6

 

Support Vector Machines

Ethics in ML

Lab 3:  SVMs, Evaluation  (i): Support Vector Machines Q&A     
(ii): Ethics Q&A

7

 

Nearest Neighbours

K-Means

GMM

 Tutorial 3: Logistic RegressionCoursework 1      
will be released		(i): K-Means Q&A     
(ii): Gaussian Mixture Models Q&A      
(iii): Nearest Neighbour Q&A 

8

 

PCA

Hierarchical Clustering

Lab 4: Clustering, PCA and Evaluation  PCA Q&A

9

 

Neural Networks Tutorial 4: SVMs and Gaussian Mixture Models  Hierarchical Clustering Q&A

10

 

Revision SessionLab 5: Neural Networks   (i) Neural Networks Q&A     
(ii) Revision class

11

 

    No class meetings
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