University Of Pretoria Computer Science Department

MIT801 - Introduction to Machine and Statistical Learning

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Reading material
Things_to_know_about_Machine_Learning.pdf
A nice paper highlighting important weaknesses of ML, and general ideas to keep in mind.
salzberg97comparing.pdf
On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach
evaluating_and_comparing.pdf
Evaluating and Comparing Classifiers: Review, Some Recommendations and Limitations
SOM in R.pdf
SOM in R
Essentials of the self-organizing map.pdf
Essentials of the SOM
Lecture slides
MIT801_L1.pdf
Lecture 1: Machine learning, k-nn classification, decision trees.
MIT801_L2.pdf
Lecture 2: Random forest, perceptron, neural network, support vector machine, self-organizing map.
Assignments
Assignment 1
assignment1_phase2.pdf
Phase II Specifications
assignment1.pdf
Specifications
data.zip
Dataset

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Module Description

In this module students will be exposed to different categories of machine and statistical learning algorithms that can be used to manipulate big data, identify trends from the da...

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Ms Anna Bosman

Lecturers

Mr Sollie Millard

Dr Frans Kanfer

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