Check out neural_nets.ipynb for the full talk and example code for building a word2vec Neural Network in Python.

• Ipython notebook, numpy, scipy, pandas, matplotlib, seaborn
• gensim (a C compiler will allow you to train more quickly, though isn't necessary).

You can easily install all of the above with Continuum Analytics' conda - if you haven't heard of it yet, we'd highly recommend taking a look!

The easiest way to install all these packages is the following, once you've gotten conda installed:

conda create --name ds30 --file environment.yaml

We use the following dataset in a few examples. Warning: It's 1.5GB, so sit back and relax while the download happens!

The Google News Model from the "pre-trained" section on this page.

To run this demo, you will need to startup an ipython notebook instance:

ipython notebook

Then go to http://localhost:8888 and click on neural_nets.ipynb.

You need visit our youtube channel.

This is meant to just give you a brief guided tour of just a few topics in data science.

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