COMP0088

6.2 Convolutional Networks

COMP0088

10.5 Outro

COMP0088

10.4 Ethics & Fairness

COMP0088

10.3 Deepfakes

COMP0088

10.2 Reinforcement Learning

COMP0088

10.1 Caveat Emptor, Cave Canem

COMP0088

9.4 Large Language Models

COMP0088

9.3 Generative Adversarial Networks

COMP0088

9.2 Autoencoders

COMP0088

9.1 Deep Learning Recap

COMP0088

8.4 Hidden Markov Models

COMP0088

8.3 Expectation-Maximisation

COMP0088

8.2 Gaussian Mixture Models

COMP0088

8.1 Latent Variables

COMP0088

7.4 Embeddings & Representation Learning

COMP0088

7.3 Principal Components Analysis

COMP0088

7.2 k-Means Clustering

COMP0088

7.1 Unsupervised Learning

COMP0088

6.4 Practicalities

COMP0088

6.3 Recurrent Networks

COMP0088

6.1 Inductive Bias

COMP0088

5.4 Activation & Initialisation

COMP0088

5.3 Backpropagation

COMP0088

5.2 Multi-Layer Perceptrons

COMP0088

4.6 Support Vector Machines

COMP0088

4.4 Soft Margin

COMP0088

4.3 Optimal Hard Margin

COMP0088

5.1 Neurons for Beginners

COMP0088

4.5 The Kernel Trick

COMP0088

4.2 Perceptrons

COMP0088