inst0060-notes

Lecture notes for INST0060 Foundation of Machine Learning and Data Science module, taught at the Department of Information Studies, University College London (UCL).

Credit

The notes are based on lectures of the lecturer Dr Luke Dickens at the Department of Information Studies, University College London (UCL). Some figures are screenshots of his lectures slides.

Structure

./md/: the original .md files of the notes. Note that the .md files are created with Typora with LaTeX embedded, which is not rendered on Github, refer to .pdf files for mathematical expressions.

./src/: the directory for attached pictures

./pdf/: the exported .pdf files

Table of Contents

Lecture	Topic	Date of Lecture	Note Completion
1	Introduction, Polynomial Curve Fitting, and Probability Theory	13/01/20	✅
2	Data, Variables and Distributions	20/01/20	✅
3	Regression in Linear Models	27/01/20	✅
4	The Multivariate Gaussian & Bayesian Regression	03/02/20	✅
5	Classification, Decisions and Discriminants	10/02/20	✅
6	Probabilistic Classification	24/02/20	✅
7	Reinforcement Learning 1: Dynamic Programming & Monte-Carlo Estimation	02/03/20	✅
8	Reinforcement Learning 2: Monte-Carlo Control, Temporal Differences and Q-Learning	09/03/20
9	Unsupervised Learning: Clustering and Mixture of Gaussians	16/03/20
10	Neural Networks	23/03/20
Supplement A	Probability Theory	N/A	✅
Supplement B1	Data, Features and Approximations	N/A	✅
Supplement B2	Model Evaluation and Selectoon	N/A