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add README and author/licence

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Adel Daouzli 4 years ago
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  1. 17
      README.md
  2. 3
      letters.py
  3. 3
      mlp.py
  4. 3
      pnmimage.py

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README.md

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# Multi-Layer Perceptron
This is a Python 3 implementation of a multi-layer perceptron using Numpy and optionally Matplotlib for cost function visualization.
It is provided under GPLv3 licence.
It implements forward-propagation and backward-propagation (gradient descent).
It allows to learn examples and trying to minimize cost function.
It provides also Momentum optimization, RMSProp optimization, Adam optimization and Forbenius norm regularization.
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++.
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.
I provide the jupyter notebook I used for some tests.

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letters.py

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__author__ = "Adel Daouzli"
__licence__ = "GPLv3"
import os
from pnmimage import PnmImage

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mlp.py

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#!/usr/bin/env python3
__author__ = "Adel Daouzli"
__licence__ = "GPLv3"
import struct
import numpy as np
try:

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pnmimage.py

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__author__ = "Adel Daouzli"
__licence__ = "GPLv3"
import struct
class PnmImage(object):

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