Index

A

Activations (class in nillanet.activations)

architecture (nillanet.model.NN attribute) arithmetic_distribution() (nillanet.distributions.Distributions method)

B

batch() (nillanet.model.NN method)

binary_crossentropy() (nillanet.loss.Loss method) binary_crossentropy_derivative() (nillanet.loss.Loss method)

D

Distributions (class in nillanet.distributions)

I

IO (class in nillanet.io)

L

learning_rate (nillanet.model.NN attribute) linear() (nillanet.activations.Activations method) linear_derivative() (nillanet.activations.Activations method)

linear_distribution() (nillanet.distributions.Distributions method) load() (nillanet.io.IO method) logical_distribution() (nillanet.distributions.Distributions method) Loss (class in nillanet.loss)

M

module nillanet.activations nillanet.distributions nillanet.io nillanet.loss nillanet.model

mse() (nillanet.loss.Loss method) mse_alt() (nillanet.loss.Loss method) mse_alt_derivative() (nillanet.loss.Loss method) mse_derivative() (nillanet.loss.Loss method)

N

nillanet.activations module nillanet.distributions module nillanet.io module

nillanet.loss module nillanet.model module NN (class in nillanet.model)

P

predict() (nillanet.model.NN method)

R

relu() (nillanet.activations.Activations method)

relu_derivative() (nillanet.activations.Activations method)

S

save() (nillanet.io.IO method) sigmoid() (nillanet.activations.Activations method) sigmoid_derivative() (nillanet.activations.Activations method)

softmax() (nillanet.activations.Activations method) sort() (nillanet.distributions.Distributions method) summary() (nillanet.model.NN method) summation() (nillanet.distributions.Distributions method)

T

tanh() (nillanet.activations.Activations method)

tanh_derivative() (nillanet.activations.Activations method) train() (nillanet.model.NN method)

W

W (nillanet.model.NN attribute)

X

X (nillanet.model.NN attribute)

Y

Y (nillanet.model.NN attribute)