# Course - Machine Learning MT23

> Source: https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/ · Updated: 2025-10-21 · Tags: uni, course

> Covers lots of topics in machine learning from a very mathematical perspective: regression, regularisation, maximum likelihood estimates, optimisation, generative models, support vector machines, neural networks and backpropagation, CNNs, principal component analysis and clustering.

- [Course Webpage](https://courses.cs.ox.ac.uk/course/view.php?name=ml_2023_2024)
- [Lecture Notes](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/lectures/)
- [Practicals](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/practicals/)
	- [Practical 1](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/practicals/practical1.pdf)
	- [Practical 2](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/practicals/practical2.pdf)
	- [Practical 3](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/practicals/practical3.pdf)
- Overlaps with: [Course - Numerical Analysis HT24](https://ollybritton.com/notes/uni/part-a/ht24/numerical-analysis/)
- The successor to the [Prelims](https://ollybritton.com/notes/uni/prelims/) course: [Course - Continuous Mathematics HT23](https://ollybritton.com/notes/uni/prelims/ht23/continuous-mathematics/)
- Other courses this term: [Courses MT23](https://ollybritton.com/notes/uni/part-a/mt23/)

### Notes
- [Notes - Machine Learning MT23, Basis expansion](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/basis-expansion/)
- [Notes - Machine Learning MT23, Bayesian machine learning](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/bayesian-machine-learning/)
- [Notes - Machine Learning MT23, Classification](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/classification/)
- [Notes - Machine Learning MT23, Clustering](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/clustering/)
- [Notes - Machine Learning MT23, Convex optimisation](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/convex-optimisation/)
- [Notes - Machine Learning MT23, Convolutional neural networks](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/convolutional-neural-networks/)
- [Notes - Machine Learning MT23, Covariance and correlation](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/covariance-and-correlation/)
- [Notes - Machine Learning MT23, Cross-entropy loss](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/cross-entropy-loss/)
- [Notes - Machine Learning MT23, Gaussian discriminant analysis](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/gaussian-discriminant-analysis/)
- [Notes - Machine Learning MT23, Generative models](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/generative-models/)
- [Notes - Machine Learning MT23, Gradient descent](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/gradient-descent/)
- [Notes - Machine Learning MT23, Inverse transform sampling](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/inverse-transform-sampling/)
- [Notes - Machine Learning MT23, Kernels](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/kernels/)
- [Notes - Machine Learning MT23, Learning curves](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/learning-curves/)
- [Notes - Machine Learning MT23, Linear regression](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/linear-regression/)
- [Notes - Machine Learning MT23, Logistic regression](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/logistic-regression/)
- [Notes - Machine Learning MT23, Matrix calculus](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/matrix-calculus/)
- [Notes - Machine Learning MT23, Maximum likelihood principle](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/maximum-likelihood-principle/)
- [Notes - Machine Learning MT23, Model selection](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/model-selection/)
- [Notes - Machine Learning MT23, Multivariate Gaussians](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/multivariate-gaussians/)
- [Notes - Machine Learning MT23, Multidimensional scaling](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/multidimensional-scaling/)
- [Notes - Machine Learning MT23, Naïve Bayes classifiers](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/naive-bayes-classifiers/)
- [Notes - Machine Learning MT23, Neural networks](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/neural-networks/)
- [Notes - Machine Learning MT23, Optimisation](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/optimisation/)
- [Notes - Machine Learning MT23, Paradigms](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/paradigms/)
- [Notes - Machine Learning MT23, Perceptrons](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/perceptrons/)
- [Notes - Machine Learning MT23, Principal component analysis](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/principal-component-analysis/)
- [Notes - Machine Learning MT23, Recurrent neural networks](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/recurrent-neural-networks/)
- [Notes - Machine Learning MT23, Singular value decomposition](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/singular-value-decomposition/)
- [Notes - Machine Learning MT23, Spectral clustering](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/spectral-clustering/)
- [Notes - Machine Learning MT23, Support vector machines](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/support-vector-machines/)
- [Notes - Machine Learning MT23, Overfitting and underfitting](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/overfitting-and-underfitting/)
- [Notes - Machine Learning MT23, k-means clustering](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/k-means-clustering/)
- [Notes - Machine Learning MT23, k-nearest neighbours](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/k-nearest-neighbours/)
- [Notes - Machine Learning MT23, Misc](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/notes/misc/)

### Problem Sheets
- [Sheet 0](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/sheets/sheet0.pdf)
- [Sheet 1](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/sheets/sheet1.pdf)
- [Sheet 2](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/sheets/sheet2.pdf)
- [Sheet 3](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/sheets/sheet3.pdf)
- [Sheet 4](https://www.cs.ox.ac.uk/teaching/materials22-23/ml/sheets/sheet4.pdf)

### Lectures
- [Lecture - Machine Learning MT23, I](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/i/)
- [Lecture - Machine Learning MT23, II](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/ii/)
- [Lecture - Machine Learning MT23, III](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/iii/)
- [Lecture - Machine Learning MT23, IV](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/iv/)
- [Lecture - Machine Learning MT23, V](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/v/)
- [Lecture - Machine Learning MT23, VI](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/vi/)
- [Lecture - Machine Learning MT23, VII](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/vii/)
- [Lecture - Machine Learning MT23, VIII](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/viii/)
- [Lecture - Machine Learning MT23, IX](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/ix/)
- [Lecture - Machine Learning MT23, X](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/x/)
- [Lecture - Machine Learning MT23, XI](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xi/)
- [Lecture - Machine Learning MT23, XII](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xii/)
- [Lecture - Machine Learning MT23, XIII](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xiii/)
- [Lecture - Machine Learning MT23, XIV](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xiv/)
- [Lecture - Machine Learning MT23, XV](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xv/)
- [Lecture - Machine Learning MT23, XVI](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xvi/)
- [Lecture - Machine Learning MT23, XVII](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xvii/)
- [Lecture - Machine Learning MT23, XVIII](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xviii/)
- [Lecture - Machine Learning MT23, XIX](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xix/)
- [Lecture - Machine Learning MT23, XX](https://ollybritton.com/notes/uni/part-a/mt23/machine-learning/lectures/xx/)

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