COMP6237 Data Mining

Notes, Slides and Demos for COMP6237 2025-26


Maintained by Dr Shoaib Ehsan and Dr Zhiwu Huang

Zhiwu’s parts of the ECS COMP6237 Data Mining module will be taught through lectures and demonstrations, based on Jon Hare’s and Jo Grundy’s lectures and demonstrations written for the course in previous years. Their demonstrations, lecture slides, and videos are available here. Please note that video recordings may not be available for all lectures. This may be due to technical issues or our intention to encourage greater in-person attendance. Additionally, some recordings may only be available for lectures from earlier years.

Side Notes: The module AICE1006-EDA Resource provides valuable insights and example codes on fundamental data processing and analysis, which may be useful for the COMP6237 coursework. The module COMP6252 Deep Learning Technologies offers a comprehensive guideline on applying basic deep learning techniques for those interested in further learning. If additional computational resources are required for training deep learning models, please refer to the Iridis Useful Scripts, which can help enhance efficiency for computationally intensive tasks.

Date Title Slides Handouts Code Video
26/01/26 Introduction to Data Mining PDF Video
29/01/26 Discovering Groups PDF git Video
30/01/26 Dimensionality Reduction I PDF git Video
02/02/26 Dimensionality Reduction II PDF git Video
03/02/26 Searching and Ranking PDF git Video
06/02/26 Linear Regression I PDF Video
16/02/26 Linear Regression II PDF Video
19/02/26 Linear Regression Problem Sets PDF Video
20/02/26 Logistic Regression PDF Video
26/02/26 Dealing with Non-Linear Data PDF
27/02/26 Recommendation Systems PDF git Video
02/03/26 Document Filtering PDF git
03/03/26 Decision Trees PDF git
06/03/26 Nearest Neighbours PDF git
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