savarin / pyconuk-introtutorial

practical introduction to Python for machine learning, with pandas and scikit-learn - Sept 2014

Pycon UK Introductory Tutorial

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.

Installation

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.

Tutorial

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.

• Section 1-0 - First Cut
• Section 1-1 - Filling-in Missing Values
• Section 1-2 - Creating Dummy Variables
• Section 1-3 - Parameter Tuning

pyconuk-introtutorial's Issues

Session1-3 mode() error

mode() raise an error when df['Embarked'] has NaN in python3,
but df['Embarked'].mode() is worked.

so, change the statement
mode_embarked = mode(df['Embarked'])[0][0]
to
mode_embarked = df['Embarked'].mode()[0]