Gradient Descent and the Backpropagation Algorithm

Gradient Descent and the Backpropagation Algorithm

Alfredo Canziani via YouTube Direct link

– Traditional neural nets

6 of 15

6 of 15

– Traditional neural nets

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Gradient Descent and the Backpropagation Algorithm

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  1. 1 – Supervised learning
  2. 2 – Parametrised models
  3. 3 – Block diagram
  4. 4 – Loss function, average loss
  5. 5 – Gradient descent
  6. 6 – Traditional neural nets
  7. 7 – Backprop through a non-linear function
  8. 8 – Backprop through a weighted sum
  9. 9 – PyTorch implementation
  10. 10 – Backprop through a functional module
  11. 11 – Backprop through a functional module
  12. 12 – Backprop in practice
  13. 13 – Learning representations
  14. 14 – Shallow networks are universal approximators!
  15. 15 – Multilayer architectures == compositional structure of data

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