Lecture slides
Lecture 1: Linear Algebra
Lecture 2: Analytic Geometry
Lecture 3: Matrix Decomposition
Lecture 4: Vector Calculus
Lecture 5: Probability and Distributions
Lecture 6: Continuous Optimisation
Lecture 7: When Models Meet Data
Lecture 8: Linear Regression
Lecture 9: Dimensionality Reduction with PCA
Lecture 10: Density Estimation with GMMs
Lecture 11: Classification with SVMs
Assignments
Assignment 1
Assignment 2, x.dat, y.dat
Assignment 3, faces.zip
Plagiarism declaration form (PDF)
Plagiarism declaration form (DOCX)