| 19 - Understand and design CNNs/005 Examine feature map activations.mp4 | 260.56 MB |
| 22 - Style transfer/004 Transferring the screaming bathtub.mp4 | 216.82 MB |
| 19 - Understand and design CNNs/012 The EMNIST dataset (letter recognition).mp4 | 201.31 MB |
| 19 - Understand and design CNNs/002 CNN to classify MNIST digits.mp4 | 200.33 MB |
| 24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/005 CodeChallenge sine wave extrapolation.mp4 | 195.67 MB |
| 24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/009 Lorem ipsum.mp4 | 192.53 MB |
| 07 - ANNs (Artificial Neural Networks)/013 Multi-output ANN (iris dataset).mp4 | 186.77 MB |
| 19 - Understand and design CNNs/004 Classify Gaussian blurs.mp4 | 185.14 MB |
| 09 - Regularization/004 Dropout regularization in practice.mp4 | 183.23 MB |
| 16 - Autoencoders/006 Autoencoder with tied weights.mp4 | 177.74 MB |
| 18 - Convolution and transformations/003 Convolution in code.mp4 | 173.1 MB |
| 08 - Overfitting and cross-validation/006 Cross-validation -- DataLoader.mp4 | 172.32 MB |
| 23 - Generative adversarial networks/002 Linear GAN with MNIST.mp4 | 169.9 MB |
| 07 - ANNs (Artificial Neural Networks)/009 Learning rates comparison.mp4 | 168.64 MB |
| 12 - More on data/003 CodeChallenge unbalanced data.mp4 | 166.26 MB |
| 11 - FFNs (Feed-Forward Networks)/003 FFN to classify digits.mp4 | 161.85 MB |
| 16 - Autoencoders/005 The latent code of MNIST.mp4 | 161.81 MB |
| 24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/004 Predicting alternating sequences.mp4 | 160.16 MB |
| 07 - ANNs (Artificial Neural Networks)/018 Model depth vs. breadth.mp4 | 158.91 MB |
| 12 - More on data/007 Data feature augmentation.mp4 | 158.27 MB |
| 21 - Transfer learning/007 Pretraining with autoencoders.mp4 | 156.58 MB |
| 14 - FFN milestone projects/004 Project 2 My solution.mp4 | 155.73 MB |
| 21 - Transfer learning/008 CIFAR10 with autoencoder-pretrained model.mp4 | 153.34 MB |
| 07 - ANNs (Artificial Neural Networks)/008 ANN for classifying qwerties.mp4 | 151.12 MB |
| 21 - Transfer learning/005 Transfer learning with ResNet-18.mp4 | 148.46 MB |
| 19 - Understand and design CNNs/008 Do autoencoders clean Gaussians.mp4 | 147.88 MB |
| 15 - Weight inits and investigations/009 Learning-related changes in weights.mp4 | 146.78 MB |
| 07 - ANNs (Artificial Neural Networks)/010 Multilayer ANN.mp4 | 144.7 MB |
| 10 - Metaparameters (activations, optimizers)/002 The wine quality dataset.mp4 | 143.5 MB |
| 08 - Overfitting and cross-validation/005 Cross-validation -- scikitlearn.mp4 | 142.88 MB |
| 26 - Where to go from here/002 How to read academic DL papers.mp4 | 141.85 MB |
| 18 - Convolution and transformations/012 Creating and using custom DataLoaders.mp4 | 139.53 MB |
| 07 - ANNs (Artificial Neural Networks)/007 CodeChallenge manipulate regression slopes.mp4 | 139.12 MB |
| 09 - Regularization/003 Dropout regularization.mp4 | 138.39 MB |
| 16 - Autoencoders/004 AEs for occlusion.mp4 | 138.2 MB |
| 10 - Metaparameters (activations, optimizers)/015 Loss functions in PyTorch.mp4 | 138.1 MB |
| 19 - Understand and design CNNs/011 Discover the Gaussian parameters.mp4 | 136.65 MB |
| 12 - More on data/001 Anatomy of a torch dataset and dataloader.mp4 | 135.84 MB |
| 23 - Generative adversarial networks/004 CNN GAN with Gaussians.mp4 | 135.7 MB |
| 12 - More on data/002 Data size and network size.mp4 | 135.67 MB |
| 06 - Gradient descent/007 Parametric experiments on g.d.mp4 | 135.61 MB |
| 07 - ANNs (Artificial Neural Networks)/006 ANN for regression.mp4 | 135.5 MB |
| 16 - Autoencoders/003 CodeChallenge How many units.mp4 | 135.38 MB |
| 15 - Weight inits and investigations/005 Xavier and Kaiming initializations.mp4 | 134.08 MB |
| 19 - Understand and design CNNs/010 CodeChallenge Custom loss functions.mp4 | 132.89 MB |
| 07 - ANNs (Artificial Neural Networks)/016 Depth vs. breadth number of parameters.mp4 | 132.07 MB |
| 18 - Convolution and transformations/011 Image transforms.mp4 | 129.9 MB |
| 24 - RNNs (Recurrent Neural Networks) (and GRULSTM)/007 GRU and LSTM.mp4 | 129.66 MB |
| 15 - Weight inits and investigations/006 CodeChallenge Xavier vs. Kaiming.mp4 | 126.5 MB |
| 12 - More on data/010 Save the best-performing model.mp4 | 126.5 MB |