GWU_Network
- class gwu_nn.gwu_network.GWUNetwork
The GWUNetwork class is the core class of the library that provies a foundation to build a network by iteratively adding layers
- add(layer)
A network is comprised of a series of layers connected together. The add method provides a means to add a layer to a network
- Args:
Layer (Layer): A Layer object to add to the network
- compile(loss, lr)
Compile sets a model’s loss function and learning rate, preparing the model for training
- Args:
loss (LossFunction): The loss function used for the network lr (float): The learning rate for the network
- fit(x_train, y_train, epochs, batch_size=None)
Fit is the trianing loop for the model/network
- Args:
x_train (np.array): Inputs for the network to train on y_train (np.array): Expected outputs for the network epochs (int): Number of training cycles to run through batch_size (int): Number of records to train on at a time
- get_weights()
Get the weights for the model
- Returns:
np.array: weights of the model
- predict(input_data)
Predict produces predictions for the provided input data
- Args:
input_data (np.array): Input data to inference
- Returns:
np.array: the predictions for the given model