R Interface to the Keras Deep Learning Library

Activation | Applies an activation function to an output. |

ActivityRegularization | Layer that applies an update to the cost function based input... |

AdvancedActivation | Advanced activation layers |

Applications | Load pre-trained models |

AveragePooling | Average pooling operation |

BatchNormalization | Batch normalization layer |

Constraints | Apply penalties on layer parameters |

Conv | Convolution layers |

Cropping | Cropping layers for 1D input (e.g. temporal sequence). |

CSVLogger | Callback that streams epoch results to a csv file. |

Datasets | Load datasets |

decode_predictions | Decode predictions from pre-defined imagenet networks |

Dense | Regular, densely-connected NN layer. |

Dropout | Applies Dropout to the input. |

EarlyStopping | Stop training when a monitored quantity has stopped... |

Embedding | Embedding layer |

expand_dims | Expand dimensions of an array |

Flatten | Flattens the input. Does not affect the batch size. |

GaussianNoise | Apply Gaussian noise layer |

GlobalPooling | Global pooling operations |

img_to_array | Converts a PIL Image instance to a Numpy array. |

Initalizers | Define the way to set the initial random weights of Keras... |

keras_available | Tests if keras is available on the system. |

keras_check | Called to check if keras is installed and loaded |

keras_compile | Compile a keras model |

keras_fit | Fit a keras model |

keras_init | Initialise connection to the keras python libraries. |

kerasR | Keras Models in R |

LayerWrapper | Layer wrappers |

load_img | Load image from a file as PIL object |

LoadSave | Load and save keras models |

LocallyConnected | Locally-connected layer |

Masking | Masks a sequence by using a mask value to skip timesteps. |

MaxPooling | Max pooling operations |

ModelCheckpoint | Save the model after every epoch. |

normalize | Normalize a Numpy array. |

one_hot | One-hot encode a text into a list of word indexes |

Optimizers | Optimizers |

pad_sequences | Pad a linear sequence for an RNN input |

Permute | Permutes the dimensions of the input according to a given... |

plot_model | Plot model architecture to a file |

Predict | Predict values from a keras model |

preprocess_input | Preprocess input for pre-defined imagenet networks |

ReduceLROnPlateau | Reduce learning rate when a metric has stopped improving. |

Regularizers | Apply penalties on layer parameters |

RepeatVector | Repeats the input n times. |

Reshape | Reshapes an output to a certain shape. |

RNN | Recurrent neural network layers |

Sequential | Initialize sequential model |

TensorBoard | Tensorboard basic visualizations. |

text_to_word_sequence | Split a sentence into a list of words. |

to_categorical | Converts a class vector (integers) to binary class matrix. |

Tokenizer | Tokenizer |

UpSampling | UpSampling layers. |

ZeroPadding | Zero-padding layers |

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