My lecture notes during times at UCL. Each of the folder contains a note for that subject: Most of them are transcription (and hopefully smaller) of the source material with some more details (such as additional prove not presented in the lecture), where we have:
- COMP0083: Advanced Topics in Machine Learning (
adv-topic-in-ml) - COMP0085: Approximate Inference and Learning in Probabilistic Models (
approx-infer) - COMP0086: Probabilistic and Unsupervised Learning (
prob-unsup) - STAT0027: Foundation Fortnight (
rice-foundation-fortnight) - STAT0028: Statistical Models and Data Analysis (
stat-analysis) - COMP0078: Supervised Learning (
supervised-learning)
In COMP0083, I also added some notes from EE364a: Convex Optimization I to refresh some of my memory for convex optimization. STAT0027, on the other hands, is wholly based on John A. Rice's Mathematical Statistics and Data Analysis.
Currently it is a draft i.e poorly worded, direct copy, bad grammar etc. There are some more courses that I took, such as: COMP0089: Reinforcement Learning, COMP0120: Numerical Optimisation and COMP0168: Machine Learning Seminar that I haven't had time to edits my notes (to a more coherent degree), stay tune!!
If there is any mistakes on my notes, feels free to make and issue and/or create a pull request.