| .. | ||
| .keep | ||
| Batch_normalization.ipynb | ||
| Impact_of_building_a_deeper_neural_network.ipynb | ||
| Impact_of_dropout.ipynb | ||
| Impact_of_regularization.ipynb | ||
| Inspecting_color_images.ipynb | ||
| Inspecting_grayscale_images.ipynb | ||
| Learning_rate_annealing.ipynb | ||
| Preparing_our_data.ipynb | ||
| Readme.md | ||
| Scaling_the_dataset.ipynb | ||
| Steps_to_build_a_neural_network_on_FashionMNIST.ipynb | ||
| Varying_batch_size.ipynb | ||
| Varying_learning_rate_on_non_scaled_data.ipynb | ||
| Varying_learning_rate_on_scaled_data.ipynb | ||
| Varying_loss_optimizer.ipynb | ||
Errata
In the notebook covering batch normalization, the second half of the experiment was missing a model.eval() in val_loss function.
Due to which the graphs were not accurate.
The graph presented in page 147 shown below
should actually be
