Keras 3 API documentation

None Getting started Developer guides Code examples Keras 3 API documentation Models API Layers API Callbacks API Ops API Optimizers Metrics Losses Data loading Tree API Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Quantizers Scope Rematerialization Utilities Keras 2 API documentation KerasTuner: Hyperparam Tuning KerasHub: Pretrained Models KerasRS Get started Guides API Examples Keras Hub Keras RS Keras Tuner Keras 3 API documentation Models API Layers API Callbacks API Ops API Optimizers Metrics Losses Data loading Tree API Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Quantizers Scope Rematerialization Utilities Keras 2 API documentation ► Keras 3 API documentation Keras 3 API documentation Models API The Model class The Sequential class Model training APIs Saving & serialization Knowledge distillation 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 OrbaxCheckpoint Ops API The Operation class NumPy ops NN ops Linear algebra ops Core ops Image ops FFT ops Einops ops Math ops Optimizers SGD RMSprop Adam AdamW Adadelta Adagrad Adamax Adafactor Nadam Ftrl Lion Lamb Loss Scale Optimizer MultiOptimizer OptimizerMap Muon 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 Probabilistic losses Regression losses Hinge losses for "maximum-margin" classification Data loading Image data loading Timeseries data loading Text data loading Audio data loading Tree API Tree utilities 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 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 Multi-device distribution LayoutMap API DataParallel API ModelParallel API Distribution utilities RNG API SeedGenerator class Random operations Quantizers Quantizer classes Quantizer utilities Scope Scope classes Context Managers Rematerialization RematScope Remat Utilities Experiment management utilities Model plotting utilities Structured data preprocessing utilities Tensor utilities Bounding boxes Python & NumPy utilities Bounding boxes utilities Visualization utilities Preprocessing utilities Backend utilities Scikit-Learn API wrappers Keras configuration utilities Keras 3 API documentation Models API Layers API Callbacks API Ops API Optimizers Metrics Losses Data loading Tree API Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Quantizers Scope Rematerialization Utilities Terms | Privacy