THIS GIT IS NOt UPDATE ! SEE TH PACKAGE ON PYPI ! THANKS TOU !

Is a simple python library to use the concept of deep learning in your project (is verrrrrrryyyyyy simple for shur)

SIMPLEPYAI

Hey guy ! I'm 15 years and a frensh dev ! I present you my project of neural network ! Just for the credit : LeLaboDuGame on Twitch -> https://twitch.tv/LeLaboDuGame You can use this library on all your project !

Now it's possible to choose an activation function, to do that you can refer at the "sigmoid" function and the "derivation_sigmoid" function

The model use the sigmoïde activation function.

HOW TO USE:

ON FIRST:

Download all of this library: pickle,matplotlib,tqdm,numpy

EXAMPLE:

x = [[1], [0]]
y = [[0], [1]]
nn = Neural_Network(x, y, layers=[1, 64, 32, 64, 1], learning_rate=0.001, activation_function=sigmoid,
                    derivation=derivation_sigmoid, reload_last_session=False)
nn.train(10000, show=True)
print(nn.predict([[1], [0]]))  # predict values

TO START:

-To init you must send 'x' and 'y' list (or numpy array).
'x' is your input and 'y' is your output.

-You must put the 'layers' (default is [2, 3, 1] 2 is the input and 1 the output neurone).
The 'layers' is a list represent all of your layers with the number of your neurone example:

[4,                                     3,4,10,1,                                       100]
 ^                                          ^                                             ^ 
 |                                          |                                             |
(is for 4 neurone in the first layer)(some layers)(And the number of neurones in the output)

-You can set the 'learning_rate' more is small more he understands, but it will take more repetition in
training.

-'reload_last_session' (default: False) is to reload the last session (if is the first sessions set to False)

TO TRAIN:

-'n_iter' is the number of train repetition

-'show' (default: True) is to show how the graphique of your model

-'save' (default: False) is to save your model (you can reload your model with the 'reload_last_session'
in init.

Thank you very much to use this library !