About Keras
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Keras 3 API documentation
Keras 2 API documentation
Models API
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Optimizers
Metrics
Losses
Probabilistic losses
Regression losses
Hinge losses for "maximum-margin" classification
Data loading
Built-in small datasets
Keras Applications
Mixed precision
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KerasTuner: Hyperparam Tuning
KerasHub: Pretrained Models
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Keras 2 API documentation
/ Losses
Losses
Probabilistic losses
BinaryCrossentropy class
CategoricalCrossentropy class
SparseCategoricalCrossentropy class
Poisson class
binary_crossentropy function
categorical_crossentropy function
sparse_categorical_crossentropy function
poisson function
KLDivergence class
kl_divergence function
Regression losses
MeanSquaredError class
MeanAbsoluteError class
MeanAbsolutePercentageError class
MeanSquaredLogarithmicError class
CosineSimilarity class
mean_squared_error function
mean_absolute_error function
mean_absolute_percentage_error function
mean_squared_logarithmic_error function
cosine_similarity function
Huber class
huber function
LogCosh class
log_cosh function
Hinge losses for "maximum-margin" classification
Hinge class
SquaredHinge class
CategoricalHinge class
hinge function
squared_hinge function
categorical_hinge function
Losses
Probabilistic losses
Regression losses
Hinge losses for "maximum-margin" classification