COMP6237 -- Data Mining

This is a summary of some lectures I gave for COMP6237 Data Mining. The slides for the lectures I gave can be found from the links below.
If you are not familiar with R and want to follow some examples from the lectures, you might want to have a look at an introductory tutorial on R I gave for another module: which you can find here .

Lecture Slides

Links to lecture slides (some slides cover more than one lecture):

Introduction lecture. Link to the recording.

Link to problem sheet for the first two lectures.

Lecture on Linear Regression and MLE. Link to the recording (part I). part II.
Tutorial recording. Link to recording .
QR factorization. Link to recording .


Link to problem sheet for the second two lectures.
Lecture on Logistic Regression, Non-Linear and Dependent Data, and Model Reduction.
Link to the recording and 2nd link .
solutions to the problem sheet. (link to recording) .



Lecture on Information Theory and Feature Extraction. (link to recording) (2nd session)
Solutions to the problems at the end of the lecture on information theory.

Lecture on Mining Data Streams.
Link to the recording.

Lectures on Data Mining and Networks.
Link to the recording of part I and a link to the recording of part II

Lecture on Link Prediction on Networks.
Link to the recording of part I and Link to the recording of part II

Lecture on Community Detection on Networks.

Lecture on Exploiting Network Structures for Information Retrieval.
Link to the recording of part I and a link to the recording of part II

Problem sheet for networks lectures.
Solutions to the problem sheet can be found here page 1, page 2, page 3, and page 4. Here is a recoding where I explain the solutions.

Scans of my lecture preparation for the seminar on networks (link prediction + pagerank) can be found here .

Revision Lecture.