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Fourth year

Machine Learning and Neural Networks

Machine learning and neural networks: regression and gradient descent, multilayer networks and backpropagation, optimisers, convolutional and recurrent networks, transformers, training in practice, NumPy and PyTorch.

8 articles

Course syllabus

8 topics, in course order

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8 of 8 topics have a complete lesson

  1. 1 Regression and gradient descent
  2. 2 Perceptron and multilayer networks
  3. 3 Backpropagation
  4. 4 Optimisers
  5. 5 Convolutional networks
  6. 6 Recurrent networks and transformers
  7. 7 Training in practice
  8. 8 Project: NumPy, PyTorch, ONNX