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Computational graph

This repo is a Python 3 implementation of a computational graph to do deep learning. I learned in that all big deep learning librairies used that principle so I wanted to understand it and to do that I implemented it.

Getting Started

Simply clone this repo

Prerequisites

Essential : Numpy

pip install numpy

Optional : Graphviz

Example

Run fully, fully_mnist, conv or conv_mnist in the terminal

This is the supposed output of the fully file.

This image represent the dataset used, it is a 2d dataset with two classes in a XOR position with a little bit of noise so that perfect separation if impossible

dataset

This image represent the graph built

graph

This image represent the exectution of the program in the terminal

cmd

This image represent the loss of the graph at each iteration

loss

This image represent the resulting decision boundary

boudary

Built With

  • Numpy - NumPy is the fundamental package for scientific computing with Python
  • Graphviz - Graph Visualization Software

Authors

  • Jean-Gabriel Simard

Acknowledgments

  • Jeremy Fix - CentraleSupélec Teacher