This tutorial is a condensed version of the one delivered at Pycon UK 2014. The original tutorial can be found here. For an introduction to neural networks, please visit Neural Networks in a Nutshell.
This tutorial requires jupyter, pandas and scikit-learn. These can be installed with pip by typing the following in terminal:
pip install jupyterlab pandas sklearn
We will be reviewing the materials with Jupyter notebooks. You should be able to type
jupyter-lab
in your terminal window and see the notebook panel load in your web browser.
The tutorial will start with data manipulation using pandas - loading and cleaning data. We'll then use scikit-learn to make predictions. By the end of the session, we would have worked on the Kaggle Titanic dataset from start to finish, through a number of iterations in an increasing order of sophistication.