Statements (52)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:API
|
| gptkbp:analyzes |
training process
|
| gptkbp:can |
training metrics
|
| gptkbp:can_adjust_learning_rate |
during training
|
| gptkbp:can_be_combined_with |
multiple callbacks
|
| gptkbp:can_be_customized_with |
by user-defined functions
|
| gptkbp:can_be_used_for |
early stopping
model checkpointing dynamic learning rate adjustment custom actions at the end of a batch custom actions at the end of an epoch custom actions at the end of training custom actions at the start of training logging training history monitoring training progress saving model architecture saving model weights saving training configuration visualization with Tensor Board |
| gptkbp:can_save_best_model |
based on validation metrics
|
| gptkbp:can_stop_training |
if a condition is met
|
| gptkbp:captures |
model weights
|
| https://www.w3.org/2000/01/rdf-schema#label |
Keras Callbacks
|
| gptkbp:includes |
gptkb:Model
gptkb:Reduce_LROn_Plateau gptkb:board_game Early Stopping CSVLogger |
| gptkbp:is_compatible_with |
gptkb:Tensor_Flow
gptkb:CNTK gptkb:Theano |
| gptkbp:is_documented_in |
Keras documentation
|
| gptkbp:is_implemented_in |
gptkb:Python
|
| gptkbp:is_part_of |
gptkb:API
Keras library |
| gptkbp:is_supported_by |
Keras community
|
| gptkbp:is_used_for |
hyperparameter tuning
performance monitoring resource management model evaluation experiment tracking training optimization adjusting training parameters controlling training flow debugging training process |
| gptkbp:is_used_in |
model.fit() method
|
| gptkbp:monitors |
validation loss
training accuracy |
| gptkbp:provides |
customization during training
|
| gptkbp:used_in |
deep learning
|
| gptkbp:bfsParent |
gptkb:tf.keras.callbacks._History
|
| gptkbp:bfsLayer |
5
|