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Data Science in 30 Minutes

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

System requirements

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

Installation

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

Pre-trained model to download (optional)

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.

Run:

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.

To follow along:

You need visit our youtube channel.

More:

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

If you enjoyed this and want to learn more about doing data science in industry, consider applying to be a fellow at The Data Incubator

If you would like to hire data scientists, introduce data science corporate training, or partner to bring The Data Incubator to your country, reach out here.