semvec/pypi-packages huggingface dataset:
nait 3.0.8
Machine learning library
License: MIT
Keywords: nait

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# Nait



Provides functions and classes for creating and<br>

training neural networks.



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* Model

* Model.train

* Model.predict

* Model.mutate

* Layer

* Layer.forward

* Layer.mutate

* Neuron

* Neuron.parse

* Neuron.mutate

* Activation

* Activation.calculate

* evaluate

* save

* load



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## Model

*class*



### Syntax



`Model(layers)` 



### Arguments



* layers `list`



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## 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`



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## Model.predict

*method*



### Syntax



`predict(inputs)`



### Arguments



* inputs `list`



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## Model.mutate

*method*



### Syntax



`mutate(rate)`



### Arguments



* rate `int / float`



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## 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`



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## Layer.mutate

*method*



### Syntax



`mutate(rate)`



### Arguments



* rate `int / float`



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## Neuron

*class*



### Syntax



`Neuron(weights, bias)`



### Arguments



* weights `list`

* bias `int / float`



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## Neuron.parse

*method*



### Syntax



`parse(inputs)`



### Arguments



* inputs `list`



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## Neuron.mutate

*method*



### Syntax



`mutate(rate)`



### Arguments



* rate `int / float`



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## Activation

*class*



### Syntax



`Activation(function)`



### Arguments



* function `"linear" / "step" / "relu" / "tanh" / "hardmax" / "sigmoid" / "softmax" / "leaky relu"`



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## Activation.calculate

*method*



### Syntax



`calculate(x)`



### Arguments



* x `int / float`



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## save

*function*



### Syntax



`save(model, path)`



### Arguments



* model `Model`

* path `str`



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## load

*function*



### Syntax



`load(path)`



### Arguments



* path `str`



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# Changelog - Nait 3.0.8



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* Fixed 'save()'



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