Numpy Multi Perceptron
This is a quick project trying to achieve a Multi-Layer Perceptron only using Numpy available features and maybe later use the Cupy library to speed up its process to GPU-Tensorflow like training speed. As mentionned it is a Multi-Layer Perceptron that is currently only using the Numpy library as its backbone and is being trained with the MNIST digit database.
This code contains :
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main.py : .py file containing the Layer_UniD ( 1D Neuron Layer ) and the MLP (Entire Model ) classes as well as the training script for a given model.
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database.py : .py file containing all the classes and functions handling the creation and extraction of data from the MNIST database.
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mnist_test.txt : Text file containing MNIST digit testing data
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mnist_train.txt : Text file containing MNIST digit training data
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model_save.txt : Text file containg an example of a save format I will try to implement at a later date ( the model cannot be saved currently ).
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Sans titre.jpg : Modifiable image that is used to test by yourself the ability of the model to predict random digits.
The model cannot be saved currently but I will try toadd that feature later using the format in model_save.txt
Prerequisites :
This code works using Numpy, Matplotlib, PIL, time and os.