Introduction to Machine Learning with IPython and scikit-learn

http://strataconf.com/strata2014/public/schedule/detail/31797

Tutorial Prerequisites

Please install the latest stable version of:

• Python (2.7 or 3.3)

• NumPy 1.6 or later

• SciPy 0.9 or later

• IPython 1.1 or later

• scikit-learn 0.14 or later

• matplotlib 1.3 or later

If have you never installed SciPy on your laptop, it might be complicated to build it from the source (you need a fortran compiler and an optimized BLAS implementation such as Atlas). In that case you should instead download a binary distribution of Python and all of the above packages called Anaconda at:

http://continuum.io/downloads

Once installed check that you can start the ipython notebook with the command:

ipython notebook

Then open a new notebook and in the first cell type (remove any leading whitespaces):

import numpy

import scipy

import matplotlib

import sklearn

print(numpy.version)

print(scipy.version)

print(matplotlib.version)

print(sklearn.version)

run the notebook cell by clicking on the run button of the notebook UI. You should get the version numbers of the installed packages.

If you get an error message please feel free to send the instructor an email at olivieratogrisel.com with the detailed error message, your operating systems version and the installation method you used.

Tutorial Description

Scikit-learn is a versatile Machine Learning library for Python that blends well with the NumPy and SciPy ecosystem and is used by a growing user-base of both academic researchers and data scientists and engineers in the tech industry.

IPython with its notebook interface is an interactive programming environment that is particularly well suited for data exploration, modelling and sharing of analysis results notably via nbviewer.ipython.org.

The objective of this tutorial is to get acquainted both with Machine Learning concepts in general and the pydata ecosystem in particular.

The session will cover the following topics:

People planning to attend this session also want to see:

• Predictive Modeling in the Cloud with Scikit-learn and IPython
• How Twitter Monitors Millions of Time-series
• Information Visualization for Large-Scale Data Workflows
• Thinking with Data

Olivier Grisel

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