# Lectures

> Source: https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/ · Updated: 2025-11-18

- [Lecture - Theories of Deep Learning MT25, II, Why deep learning](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/learning/)
- [Lecture - Theories of Deep Learning MT25, III, Exponential expressivity with depth](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/depth/)
- [Lecture - Theories of Deep Learning MT25, IV, Data classes for which DNNs can overcome the curse of dimensionality](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/dimensionality/)
- [Lecture - Theories of Deep Learning MT25, V, Controlling the exponential growth of variance and correlation](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/correlation/)
- [Lecture - Theories of Deep Learning MT25, VI, Controlling the variance of the Jacobian's spectrum](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/spectrum/)
- [Lecture - Theories of Deep Learning MT25, VII, Stochastic gradient descent and its extensions](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/extensions/)
- [Lecture - Theories of Deep Learning MT25, VIII, Optimisation algorithms for training DNNs](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/dnns/)
- [Lecture - Theories of Deep Learning MT25, XI, Visualising the filters and response in a CNN](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/cnn/)
- [Lecture - Theories of Deep Learning MT25, XII, The scattering transform and into auto-encoders](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/auto-encoders/)
- [Lecture - Theories of Deep Learning MT25, XIII, Autoencoders](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/autoencoders/)
- [Lecture - Theories of Deep Learning MT25, XIV, Generative adversarial networks](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/networks/)
- [Lecture - Theories of Deep Learning MT25, XV, A few things we missed and a summary](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/summary/)
- [Lecture - Theories of Deep Learning MT25, XVI, Ingredients for a successful mini-project report](https://ollybritton.com/notes/uni/part-c/mt25/theories-of-deep-learning/lectures/report/)

---
Olly Britton — https://ollybritton.com. Machine-readable index: https://ollybritton.com/llms.txt