- 01. Introducing Jeremy
- 02. Section 1: Motivation for RNNs
- 03. Motivation for RNNs
- 04. Vanilla supervised learners and structured input
- 05. Section 2: Motivating and Modelling Recursive Sequences
- 06. Motivating and modeling recursive sequences
- 07. Simple recursive examples
- 08. Recursive or not? Part 1
- 09. Recursive or not? Part 2
- 10. Recursive or not? Part 3
- 11. Ways of thinking about recursivity
- 12. Driving a recursive sequence
- 13. Section summary
- 14. Section 3: Injecting recursivity into a learner (the lazy wa
- 15. Injecting Recursivity into a Learner (the lazy way)
- 16. A first example
- 17. Setting up the example
- 18. Windowing the example sequence
- 19. Using Keras for fitting
- 20. Using a regressor as a generative model
- 21. A second example
- 22. Setting up the second example
- 23. Wrapping up the second example
- 24. Interesting twists on the second example
- 25. Real time series example
- 26. Section summary
- 27. Section 4: Injecting Recursivity into Learners the Smart Way
- 28. Coding up a crazy recursive sequence
- 29. Flaws with the FNN approach
- 30. RNN fundamental derivations
- 31. Formulating a Least Squares loss
- 32. RNNs and memory
- 33. RNNs and graphical models
- 34. RNN Technical Issues
- 35. Section and course summary
- 36. Outro