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Learning Data Mining with Python

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

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Product type Paperback
Published in Jul 2015
Publisher Packt
ISBN-13 9781784396053
Length 344 pages
Edition 1st Edition
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Author (1):
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Robert Layton Robert Layton
Author Profile Icon Robert Layton
Robert Layton
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Table of Contents (15) Chapters Close

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...

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