You're reading from Learning Data Mining with Python Harness the power of Python to analyze data and create insightful predictive models

Product type Paperback

Published in Jul 2015

Publisher Packt

ISBN-13 9781784396053

Length 344 pages

Edition 1st Edition

Languages

Python

Tools

IPython

Concepts

Data Mining

Author (1):

Robert Layton

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Table of Contents (15) Chapters

Preface

1. Getting Started with Data Mining FREE CHAPTER

2. Classifying with scikit-learn Estimators

3. Predicting Sports Winners with Decision Trees

4. Recommending Movies Using Affinity Analysis

5. Extracting Features with Transformers

6. Social Media Insight Using Naive Bayes

7. Discovering Accounts to Follow Using Graph Mining

8. Beating CAPTCHAs with Neural Networks

9. Authorship Attribution

10. Clustering News Articles

11. Classifying Objects in Images Using Deep Learning

12. Working with Big Data

A. Next Steps…

Index

Setting up the environment

When you have connected to the instance, you can install the updated Lasagne and nolearn packages.

First, clone the git repository for Lasagne, as was outlined earlier in this chapter:

git clone https://github.com/Lasagne/Lasagne.git

In order to build this library on this machine, we will need setuptools for Python 3, which we can install via apt-get, which is Ubuntu's method of installing applications and libraries; we also need the development library for NumPy. Run the following in the command line of the virtual machine:

sudo apt-get install python3-pip python3-numpy-dev

Next, we install Lasagne. First, we change to the source code directory and then run setup.py to build and install it:

cd Lasagne
sudo python3 setup.py install

Note

We have installed Lasagne and will install nolearn as system-wide packages for simplicity. For those wanting a more portable solution, I recommend using virtualenv to install these packages. It will allow you to use different python...