Keras 2 API documentation

None 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 Hub Keras RS Keras Tuner 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 Terms | Privacy