18 lines
850 B
Markdown
18 lines
850 B
Markdown
# Multi-Layer Perceptron
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This is a Python 3 implementation of a multi-layer perceptron using Numpy and optionally Matplotlib for cost function visualization.
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It is provided under GPLv3 licence.
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It implements forward-propagation and backward-propagation (gradient descent).
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It allows to learn examples and trying to minimize cost function.
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It provides also Momentum optimization, RMSProp optimization, Adam optimization and Forbenius norm regularization.
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Note: I developed this only to implement myself the algorithms for fun and not for any production purpose. I already coded MLPs years ago in C and in C++.
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I tested it with images of characters (in PGM format) extracted from a scanned image with an other program I developed many years ago in C++ but very dirty so I don't provide it.
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I provide the jupyter notebook I used for some tests.
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