PDC4S:\IT\DATA SCIENCE AND MACHINE LEARNING\[Guvi.in] Deep Learning Course\DL#109 - Deep Convolutional Neural Networks

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PDFs12/22/2021 10:38 PM
1. CNN Architectures - Part 1 - Setting the context.ts23,034 KB12/12/2021 3:34 AM
10. CNN Architectures - Part 2 - 1x1 Convolutions.ts38,815 KB12/12/2021 3:34 AM
11. CNN Architectures - Part 2 - The Intuition behind GoogLeNet.ts20,890 KB12/12/2021 3:34 AM
12. CNN Architectures - Part 2 - The Inception Module.ts75,417 KB12/12/2021 3:34 AM
13. CNN Architectures - Part 2 - The GoogleNet Architecture.ts38,416 KB12/12/2021 3:34 AM
14. CNN Architectures - Part 2 - Average Pooling.ts17,243 KB12/12/2021 3:34 AM
15. CNN Architectures - Part 2 - Auxiliary Loss for training a deep network.ts17,306 KB12/12/2021 3:34 AM
16. CNN Architectures - Part 2 - ResNet.ts12,711 KB12/12/2021 3:34 AM
17. Building CNN Architectures Using Pytorch - Outline.ts18,121 KB12/12/2021 3:34 AM
18. Building CNN Architectures Using Pytorch - Image Transforms.ts29,520 KB12/12/2021 3:34 AM
19. Building CNN Architectures Using Pytorch - VGG.ts24,608 KB12/12/2021 3:34 AM
2. CNN Architectures - Part 1 - The Imagenet Challenge.ts55,684 KB12/12/2021 3:34 AM
20. Building CNN Architectures Using Pytorch - Training VGG.ts15,672 KB12/12/2021 3:34 AM
21. Building CNN Architectures Using Pytorch - Pre-trained Models.ts27,654 KB12/12/2021 3:34 AM
22. Building CNN Architectures Using Pytorch - Checkpointing Models.ts27,746 KB12/12/2021 3:34 AM
23. Building CNN Architectures Using Pytorch - ResNet.ts21,138 KB12/12/2021 3:34 AM
24. Building CNN Architectures Using Pytorch - Inception Part 1.ts13,288 KB12/12/2021 3:34 AM
25. Building CNN Architectures Using Pytorch - Inception Part 2.ts22,268 KB12/12/2021 3:34 AM
26. Building CNN Architectures Using Pytorch - Exercises.ts65,533 KB12/12/2021 3:34 AM
27. Visualising CNNs - Receptive field of a neuron.ts61,648 KB12/12/2021 3:34 AM
28. Visualising CNNs - Identifying images which cause certain neurons to fire.ts62,595 KB12/12/2021 3:34 AM
29. Visualising CNNs - Visualising filters.ts46,841 KB12/12/2021 3:34 AM
3. CNN Architectures - Part 1 - Understanding the first layer of AlexNet.ts35,830 KB12/12/2021 3:34 AM
30. Visualising CNNs - Occlusion experiments.ts29,948 KB12/12/2021 3:34 AM
31. Visualising CNNs Using Python - Outline.ts8,614 KB12/12/2021 3:34 AM
32. Visualising CNNs Using Python - Custom Torchvision Dataset.ts29,043 KB12/12/2021 3:34 AM
33. Visualising CNNs Using Python - Visualising inputs.ts29,942 KB12/12/2021 3:34 AM
34. Visualising CNNs Using Python - Occlusion.ts29,450 KB12/12/2021 3:34 AM
35. Visualising CNNs Using Python - Visualising filters.ts20,403 KB12/12/2021 3:34 AM
36. Visualising CNNs Using Python - Visualising filters - code.ts8,563 KB12/12/2021 3:34 AM
37. Batch Normalization and Dropout - Normalizing inputs.ts41,676 KB12/12/2021 3:34 AM
38. Batch Normalization and Dropout - Why should we normalize the inputs.ts104,625 KB12/12/2021 3:34 AM
39. Batch Normalization and Dropout - Batch Normalization.ts83,605 KB12/12/2021 3:34 AM
4. CNN Architectures - Part 1 - Understanding all layers of AlexNet.ts32,572 KB12/12/2021 3:34 AM
40. Batch Normalization and Dropout - Learning Mu and Sigma.ts30,069 KB12/12/2021 3:34 AM
41. Batch Normalization and Dropout - Ensemble Methods.ts51,912 KB12/12/2021 3:34 AM
42. Batch Normalization and Dropout - The idea of dropout.ts34,808 KB12/12/2021 3:34 AM
43. Batch Normalization and Dropout - Training without dropout.ts119,313 KB12/12/2021 3:34 AM
44. Batch Normalization and Dropout - How does weight sharing help.ts45,222 KB12/12/2021 3:34 AM
45. Batch Normalization and Dropout - Using dropout at test time.ts12,399 KB12/12/2021 3:34 AM
46. Batch Normalization and Dropout - How does dropout act as a regularizer.ts30,070 KB12/12/2021 3:34 AM
47. Batch Normalization and Dropout - Summary and what next.ts15,550 KB12/12/2021 3:34 AM
48. Batch Normalization and Dropout Using Python - Outline and Dataset.ts9,314 KB12/12/2021 3:34 AM
49. Batch Normalization and Dropout Using Python - Batch Norm Layer.ts31,631 KB12/12/2021 3:34 AM
5. CNN Architectures - Part 1 - ZFNet.ts87,434 KB12/12/2021 3:34 AM
50. Batch Normalization and Dropout Using Python - Batch Norm Visualisation.ts25,348 KB12/12/2021 3:34 AM
51. Batch Normalization and Dropout Using Python - Batch Norm 2d.ts21,594 KB12/12/2021 3:34 AM
52. Batch Normalization and Dropout Using Python - Dropout layer.ts17,584 KB12/12/2021 3:34 AM
53. Batch Normalization and Dropout Using Python - Dropout Visualisation and Exercises.ts13,381 KB12/12/2021 3:34 AM
54. Hyperparameter Tuning and MLFlow - Outline.ts11,152 KB12/12/2021 3:34 AM
55. Hyperparameter Tuning and MLFlow - Colab on Local Runtime.ts12,270 KB12/12/2021 3:34 AM
56. Hyperparameter Tuning and MLFlow - MLFlow installation and basic usage.ts27,117 KB12/12/2021 3:34 AM
57. Hyperparameter Tuning and MLFlow - Hyperparamater Tuning.ts24,978 KB12/12/2021 3:34 AM
58. Hyperparameter Tuning and MLFlow - Refined Search for Hyperparameters.ts36,113 KB12/12/2021 3:34 AM
59. Hyperparameter Tuning and MLFlow - Logging Image Artifacts.ts15,782 KB12/12/2021 3:34 AM
6. CNN Architectures - Part 1 - VGGNet.ts35,245 KB12/12/2021 3:34 AM
60. Hyperparameter Tuning and MLFlow - Logging and Loading Models.ts19,089 KB12/12/2021 3:34 AM
61. Hyperparameter Tuning and MLFlow - One Last Visualisation.ts45,947 KB12/12/2021 3:34 AM
7. CNN Architectures - Part 1 - Summary.ts51,235 KB12/12/2021 3:34 AM
8. CNN Architectures - Part 2 - Setting the context.ts19,138 KB12/12/2021 3:34 AM
9. CNN Architectures - Part 2 - Number of computations in a convolution layer.ts63,222 KB12/12/2021 3:34 AM