PDC4S:\IT\DATA SCIENCE AND MACHINE LEARNING\[Guvi.in] Deep Learning Course\DL#110 - Sequence Models

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PDFs12/22/2021 10:41 PM
1. Sequence Learning Problems - Setting the context.ts53,794 KB12/12/2021 3:34 AM
10. Recurrent Neural Networks - Setting the context.ts33,183 KB12/12/2021 3:34 AM
11. Recurrent Neural Networks - Data and Tasks - Sequence Classification - Part 1.ts28,158 KB12/12/2021 3:34 AM
12. Recurrent Neural Networks - Data and Tasks - Sequence Classification - Part 2.ts15,310 KB12/12/2021 3:34 AM
13. Recurrent Neural Networks - A clarification about padding.ts43,789 KB12/12/2021 3:34 AM
14. Recurrent Neural Networks - Data and Tasks - Sequence Labelling.ts25,884 KB12/12/2021 3:34 AM
15. Recurrent Neural Networks - Model.ts31,170 KB12/12/2021 3:34 AM
16. Recurrent Neural Networks - Loss Function.ts38,343 KB12/12/2021 3:34 AM
17. Recurrent Neural Networks - Learning Algorithm.ts39,174 KB12/12/2021 3:34 AM
18. Recurrent Neural Networks - Learning Algorithm - Derivatives w.r.t. V.ts64,759 KB12/12/2021 3:34 AM
19. Recurrent Neural Networks - Learning Algorithm - Derivatives w.r.t. W.ts25,883 KB12/12/2021 3:34 AM
2. Sequence Learning Problems - Introduction to sequence learning problems.ts36,148 KB12/12/2021 3:34 AM
20. Recurrent Neural Networks - Evaluation.ts44,079 KB12/12/2021 3:34 AM
21. Recurrent Neural Networks - Summary and what next.ts61,968 KB12/12/2021 3:34 AM
22. Vanishing and Exploding Gradients - Revisiting the gradient wrt W.ts12,860 KB12/12/2021 3:34 AM
23. Vanishing and Exploding Gradients - Zooming into one element of the chain rule - Part 1.ts16,612 KB12/12/2021 3:34 AM
24. Vanishing and Exploding Gradients - Zooming into one element of the chain rule - Part 2.ts26,066 KB12/12/2021 3:34 AM
25. Vanishing and Exploding Gradients - A small detour to calculus.ts20,598 KB12/12/2021 3:34 AM
26. Vanishing and Exploding Gradients - Looking at the magnitude of the derivative.ts29,793 KB12/12/2021 3:34 AM
27. Vanishing and Exploding Gradients - Exploding and vanishing gradients.ts20,924 KB12/12/2021 3:34 AM
28. Vanishing and Exploding Gradients - Summary and what next.ts24,978 KB12/12/2021 3:34 AM
29. LSTMs and GRUs - Dealing with longer sequences.ts22,710 KB12/12/2021 3:34 AM
3. Sequence Learning Problems - Some more examples of sequence learning problems.ts31,889 KB12/12/2021 3:34 AM
30. LSTMs and GRUs - The white board analogy.ts6,744 KB12/12/2021 3:34 AM
31. LSTMs and GRUs - Real world example of longer sequences.ts20,544 KB12/12/2021 3:34 AM
32. LSTMs and GRUs - Going back to RNNs.ts31,338 KB12/12/2021 3:34 AM
33. LSTMs and GRUs - Selective Write - Part 1.ts22,182 KB12/12/2021 3:34 AM
34. LSTMs and GRUs - Selective Write - Part 2.ts10,899 KB12/12/2021 3:34 AM
35. LSTMs and GRUs - Selective Read.ts23,827 KB12/12/2021 3:34 AM
36. LSTMs and GRUs - Selective forget.ts24,342 KB12/12/2021 3:34 AM
37. LSTMs and GRUs - An example computation with LSTMs.ts11,501 KB12/12/2021 3:34 AM
38. LSTMs and GRUs - Gated recurrent units.ts34,718 KB12/12/2021 3:34 AM
39. LSTMs and GRUs - Summary and what next.ts41,884 KB12/12/2021 3:34 AM
4. Sequence Learning Problems - Sequence learning problems using video and speech data.ts33,647 KB12/12/2021 3:34 AM
40. Sequence Models in PyTorch - OutlineSequence Models in PyTorch - Outline.ts26,839 KB12/12/2021 3:34 AM
41. Sequence Models in PyTorch - Dataset and Task.ts18,019 KB12/12/2021 3:34 AM
42. Sequence Models in PyTorch - RNN Model.ts21,282 KB12/12/2021 3:34 AM
43. Sequence Models in PyTorch - Inference on RNN.ts45,373 KB12/12/2021 3:34 AM
44. Sequence Models in PyTorch - Training RNN.ts22,984 KB12/12/2021 3:34 AM
45. Sequence Models in PyTorch - Training Setup.ts26,355 KB12/12/2021 3:34 AM
46. Sequence Models in PyTorch - LSTM.ts22,079 KB12/12/2021 3:34 AM
47. Sequence Models in PyTorch - GRU and Exercises.ts25,990 KB12/12/2021 3:34 AM
48. Addressing the problem of vansihing and exploding gradients - Quick Recap.ts44,375 KB12/12/2021 3:34 AM
49. Addressing the problem of vansihing and exploding gradients - Intuition - How gates help to solve the problem of vanishing gradients.ts13,727 KB12/12/2021 3:34 AM
5. Sequence Learning Problems - A wishlist for modelling sequence learning problems.ts49,931 KB12/12/2021 3:34 AM
50. Addressing the problem of vansihing and exploding gradients - Revisiting vanishing gradients in RNNs.ts35,074 KB12/12/2021 3:34 AM
51. Addressing the problem of vansihing and exploding gradients - Dependency diagram for LSTMs.ts41,695 KB12/12/2021 3:34 AM
52. Addressing the problem of vansihing and exploding gradients - Computing the gradient.ts21,344 KB12/12/2021 3:34 AM
53. Addressing the problem of vansihing and exploding gradients - When do the gradients vanish.ts15,991 KB12/12/2021 3:34 AM
54. Addressing the problem of vansihing and exploding gradients - Dealing with exploding gradients.ts31,719 KB12/12/2021 3:34 AM
55. Addressing the problem of vansihing and exploding gradients - Summary and what next.ts31,953 KB12/12/2021 3:34 AM
56. Batching for Sequence Models in Pytorch - Overview.ts15,468 KB12/12/2021 3:34 AM
57. Batching for Sequence Models in Pytorch - Recap on Sequence Models.ts20,570 KB12/12/2021 3:34 AM
58. Batching for Sequence Models in Pytorch - Batching for Sequence Models.ts12,543 KB12/12/2021 3:34 AM
59. Batching for Sequence Models in Pytorch - Padding Vector Representations.ts27,159 KB12/12/2021 3:34 AM
6. Sequence Learning Problems - Intuition behind RNNs - Part 1.ts7,557 KB12/12/2021 3:34 AM
60. Batching for Sequence Models in Pytorch - Packing in PyTorch.ts33,000 KB12/12/2021 3:34 AM
61. Batching for Sequence Models in Pytorch - Training with Batched Input.ts20,158 KB12/12/2021 3:34 AM
7. Sequence Learning Problems - Intuition behind RNNs - Part 2.ts25,242 KB12/12/2021 3:34 AM
8. Sequence Learning Problems - Introducing RNNs.ts22,312 KB12/12/2021 3:34 AM
9. Sequence Learning Problems - Summary and what next.ts36,959 KB12/12/2021 3:34 AM