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Getting started
Developer guides
Code examples
Keras 3 API documentation
Keras 2 API documentation
Models API
Layers API
Callbacks API
Optimizers
Metrics
Losses
Data loading
Built-in small datasets
Keras Applications
Mixed precision
Utilities
KerasTuner: Hyperparam Tuning
KerasHub: Pretrained Models
KerasRS
Get started
Guides
API
Examples
Keras Tuner
Keras RS
Keras Hub
Keras 3 API documentation
Keras 2 API documentation
Models API
Layers API
Callbacks API
Optimizers
Metrics
Losses
Data loading
Built-in small datasets
Keras Applications
Mixed precision
Utilities
►
Keras 2 API documentation
Keras 2 API documentation
Models API
The Model class
The Sequential class
Model training APIs
Saving & serialization
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
Callbacks API
Base Callback class
ModelCheckpoint
BackupAndRestore
TensorBoard
EarlyStopping
LearningRateScheduler
ReduceLROnPlateau
RemoteMonitor
LambdaCallback
TerminateOnNaN
CSVLogger
ProgbarLogger
Optimizers
SGD
RMSprop
Adam
AdamW
Adadelta
Adagrad
Adamax
Adafactor
Nadam
Ftrl
Metrics
Accuracy metrics
Probabilistic metrics
Regression metrics
Classification metrics based on True/False positives & negatives
Image segmentation metrics
Hinge metrics for "maximum-margin" classification
Losses
Probabilistic losses
Regression losses
Hinge losses for "maximum-margin" classification
Data loading
Image data loading
Timeseries data loading
Text data loading
Audio 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
Boston 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
Mixed precision policy API
LossScaleOptimizer
Utilities
Model plotting utilities
Structured data preprocessing utilities
Python & NumPy utilities
Backend utilities
Keras 2 API documentation
Models API
Layers API
Callbacks API
Optimizers
Metrics
Losses
Data loading
Built-in small datasets
Keras Applications
Mixed precision
Utilities