Machine
Learning / Extended – 2015/16

Syllabus pages:
Machine
Learning, Machine
Learning Extended – these pages include the recommended textbooks.

**CA marks: **Bonus 1 Bonus 2 ClassTest+Take
Home Test. The Type 2 Assignment marks are in Canvas along with feedback
comments where applicable.

**Math refreshers****:**

**Lecture handouts:**

I. Introduction.
Admin & Structure of
the module; Induction slides

Check out: Tom Mitchell: The
discipline of Machine Learning & a recent short video

II. Supervised
learning methods

o
Methods of classification:
generative, discriminative; global, local; probabilistic, non-probabilistic

1. Bayes rule. Intro to
generative classification. + Exercise Sheet
(non-assessed) Solutions

2. Generative classifiers:
The Gaussian classifier + Example

Type
2 Assignment 1 + Code + gauss.m

3. K-Nearest Neighbours methods Worksheet (non-assessed) Solutions

4. Discriminative classifiers:
Intro to Support Vector Machines + Worksheet
(non-assessed) Solutions

Suite of exercises preparatory for the class test. Solutions – guest exercise class by Momodou Sanyang

The Class Test was on Friday 13 November. Open
book. [15%] Test questions
+ Model solutions

Type
2 Assignment 2 + data + code

III. Unsupervised
learning methods

o
Gaussian mixtures and
the EM algorithm – guest lecture by Alastair Turl

Type
2 Assignment 3 + code&data

IV. Intro to
Statistical Learning Theory: The
PAC model of learning in finite hypothesis classes + proof

Take home test Test questions [5%]

V. Ensemble
methods: Boosting

Learn
more: Top
10 Algorithms for Data Mining

**Additional resources**

Example exam paper from 2012 (obsolete,
since ML was a 2^{nd} year module and the content is now different)

Andrew Ng on Coursera

The `Matrix Cookbook’ – useful matrix and vector manipulation
formulae

Notes from my talk at SoCS Training for Research: Machine
Learning Concepts & Techniques

MatLab tutorials:

http://www.cyclismo.org/tutorial/matlab/

http://users.rowan.edu/~shreek/networks1/matlabintro.html

http://www.mathworks.com/access/helpdesk/help/pdf_doc/matlab/getstart.pdf

Previous years Machine
Learning page – for the curious – now obsolete.