► Keras 3 API documentation
Keras 3 API documentation
Models API
Layers API
- The base Layer class
- Layer activations
- Layer weight initializers
- Layer weight regularizers
- Layer weight constraints
- Core layers
- Convolution layers
- Pooling layers
- Recurrent layers
- Preprocessing layers
- Normalization layers
- Regularization layers
- Attention layers
- Reshaping layers
- Merging layers
- Activation layers
- Backend-specific layers
Callbacks API
- Base Callback class
- ModelCheckpoint
- BackupAndRestore
- TensorBoard
- EarlyStopping
- LearningRateScheduler
- ReduceLROnPlateau
- RemoteMonitor
- LambdaCallback
- TerminateOnNaN
- CSVLogger
- ProgbarLogger
- SwapEMAWeights
Ops API
Optimizers
Metrics
- Base Metric class
- Accuracy metrics
- Probabilistic metrics
- Regression metrics
- Classification metrics based on True/False positives & negatives
- Image segmentation metrics
- Hinge metrics for "maximum-margin" classification
- Metric wrappers and reduction metrics
Losses
Data loading
Built-in small datasets
- MNIST digits classification dataset
- CIFAR10 small images classification dataset
- CIFAR100 small images classification dataset
- IMDB movie review sentiment classification dataset
- Reuters newswire classification dataset
- Fashion MNIST dataset, an alternative to MNIST
- California Housing price regression dataset
Keras Applications
- Xception
- EfficientNet B0 to B7
- EfficientNetV2 B0 to B3 and S, M, L
- ConvNeXt Tiny, Small, Base, Large, XLarge
- VGG16 and VGG19
- ResNet and ResNetV2
- MobileNet, MobileNetV2, and MobileNetV3
- DenseNet
- NasNetLarge and NasNetMobile
- InceptionV3
- InceptionResNetV2
Mixed precision
Multi-device distribution
RNG API
Utilities
- Experiment management utilities
- Model plotting utilities
- Structured data preprocessing utilities
- Tensor utilities
- Python & NumPy utilities
- Keras configuration utilities