Nait
Provides functions and classes for creating and
training neural networks.
-
Model
-
Model.train
-
Model.predict
-
Model.mutate
-
Layer
-
Layer.forward
-
Layer.mutate
-
Neuron
-
Neuron.parse
-
Neuron.mutate
-
Activation
-
Activation.calculate
-
evaluate
-
save
-
load
Model
class
Syntax
Model(layers)
Arguments
- layers
list
Model.train
method
Syntax
train(x=[], y=[], epochs=5000, rate=1, batch_size=10, sample_size=None, square_loss=True, visual=True, loss_function=None)
Arguments
-
x
list -
y
list -
epochs
int -
rate
int / float -
batch_size
int -
sample_size
int -
square_loss
bool -
visual
bool -
loss_function
function
Model.predict
method
Syntax
predict(inputs)
Arguments
- inputs
list
Model.mutate
method
Syntax
mutate(rate)
Arguments
- rate
int / float
Layer
class
Syntax
Layer(inputs=4, neurons=4, activation="linear")
Arguments
-
inputs
int -
neurons
int -
activation
"linear" / "step" / "relu" / "tanh" / "hardmax" / "sigmoid" / "softmax" / "leaky relu"
Layer.forward
method
Syntax
forward(inputs)
Arguments
- inputs
list
Layer.mutate
method
Syntax
mutate(rate)
Arguments
- rate
int / float
Neuron
class
Syntax
Neuron(weights, bias)
Arguments
-
weights
list -
bias
int / float
Neuron.parse
method
Syntax
parse(inputs)
Arguments
- inputs
list
Neuron.mutate
method
Syntax
mutate(rate)
Arguments
- rate
int / float
Activation
class
Syntax
Activation(function)
Arguments
- function
"linear" / "step" / "relu" / "tanh" / "hardmax" / "sigmoid" / "softmax" / "leaky relu"
Activation.calculate
method
Syntax
calculate(x)
Arguments
- x
int / float
save
function
Syntax
save(model, path)
Arguments
-
model
Model -
path
str
load
function
Syntax
load(path)
Arguments
- path
str
Changelog - Nait 3.0.8
- Fixed 'save()'
1 maintainer
Metadata
1 maintainer
Release files for nait 3.0.8
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Release files / nait-3.0.8.tar.gz
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| Uploaded via |
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Security for nait 3.0.8
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