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neural_networks

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This is the code for "Neural Networks - The Math of Intelligence #4" by Siraj Raval on Youtube

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# neural_networks
This is the code for "Neural Networks - The Math of Intelligence #4" by Siraj Raval on Youtube

## Coding Challenge - Due Date, Thursday July 13 at 12 PM PST

Create your own self organizing map implementation using numpy. Bonus points if you put your code in a Jupyter notebook and document your steps well. You can use any dataset you like, [here](https://archive.ics.uci.edu/ml/datasets.html?area=&att=&format=&numAtt=&numIns=&sort=nameUp&task=clu&type=&view=table) is a good place to find some datasets. Post your Github link in the comments section of the video. Good luck!

## Overview

This is the code for [this](https://youtu.be/ov_RkIJptwE) video on Youtube by Siraj Raval as part of The Math of Intelligence Series. I go over 4 different neural networks in the video, and you can find them in this repository.

## Dependencies

* numpy
* copy
* pil

Install dependencies using [pip](https://pip.pypa.io/en/stable/)

## Usage

The simple AF notebook contains the code for the network with the added hidden layer. For the simplest version, see [this](http://iamtrask.github.io/2015/07/12/basic-python-network/). The Recurrent notebook contains the recurrent code and the self organizing map contains the code for the unsupervised model.

Type `jupyter notebook` in the terminal in the main directory and the code will appear in your browser. Install jupyter from [here](http://jupyter.readthedocs.io/en/latest/install.html) if you haven't yet.

## Credits

Credits go to [Trask](http://iamtrask.github.io/2015/07/12/basic-python-network/) and [Litery](https://github.com/Litery). I've merely created a wrapper to get people started.

## Python 2/3 Troubleshooting

## Conda
Install Conda https://conda.io/docs/installation.html

//OSX / Linux Windows
conda create -n maths python=3.5
source activate maths
conda install pandas matplotlib jupyter notebook scipy scikit-learn nb_conda

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