| custom_train_step_in_jax.ipynb | 15.4 KB | |
| custom_train_step_in_tensorflow.ipynb | 23.1 KB | |
| custom_train_step_in_torch.ipynb | 24.2 KB | |
| customizing_saving_and_serialization.ipynb | 15.8 KB | |
| customizing_what_happens_in_fit.ipynb | 22.4 KB | |
| distributed_training.ipynb | 22.5 KB | |
| distributed_training_with_jax.ipynb | 13.4 KB | |
| distributed_training_with_tensorflow.ipynb | 14.1 KB | |
| distributed_training_with_torch.ipynb | 13.1 KB | |
| distribution.ipynb | 14 KB | |
| functional_api.ipynb | 43.9 KB | |
| gptq_quantization_in_keras.ipynb | 8.2 KB | |
| int4_quantization_in_keras.ipynb | 17.1 KB | |
| int8_quantization_in_keras.ipynb | 10.5 KB | |
| intro_to_keras_for_engineers.ipynb | 18.2 KB | |
| intro_to_keras_for_researchers.ipynb | 55.7 KB | |
| keras_cv/ | - | |
| keras_hub/ | - | |
| keras_nnx_guide.ipynb | 15.3 KB | |
| keras_tuner/ | - | |
| making_new_layers_and_models_via_subclassing.ipynb | 31.5 KB | |
| migrating_to_keras_3.ipynb | 44.3 KB | |
| orbax_checkpoint.ipynb | 11.5 KB | |
| preprocessing_layers.ipynb | 32 KB | |
| quantization_overview.ipynb | 11.7 KB | |
| requirements.txt | 17 bytes | |
| sequential_model.ipynb | 17.8 KB | |
| serialization_and_saving.ipynb | 36.2 KB | |
| training_with_built_in_methods.ipynb | 62.3 KB | |
| transfer_learning.ipynb | 29.5 KB | |
| understanding_masking_and_padding.ipynb | 18.8 KB | |
| working_with_rnns.ipynb | 29.4 KB | |
| writing_a_custom_training_loop_in_jax.ipynb | 25.5 KB | |
| writing_a_custom_training_loop_in_tensorflow.ipynb | 27 KB | |
| writing_a_custom_training_loop_in_torch.ipynb | 19.1 KB | |
| writing_a_training_loop_from_scratch.ipynb | 27.3 KB | |
| writing_quantization_compatible_layers.ipynb | 27.7 KB | |
| writing_your_own_callbacks.ipynb | 18.9 KB | |
