Book Image

Learning Data Mining with Python - Second Edition

By : Robert Layton
Book Image

Learning Data Mining with Python - Second Edition

By: Robert Layton

Overview of this book

This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK. You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now. With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Extracting the blog posts


We are first going to create a MapReduce program that will extract each of the posts from each blog file and store them as separate entries. As we are interested in the gender of the author of the posts, we will extract that too and store it with the post.

Note

We can't do this in a Jupyter Notebook, so instead open a Python IDE for development. If you don't have a Python IDE you can use a text editor. I recommend PyCharm, although it has a larger learning curve and it is probably a bit heavy for just this chapter's code.

At the very least, I recommend using an IDE that has syntax highlighting and basic completion of variable names (that last one helps find typos in your code easily.

Note

If you still can't find an IDE you like, you can write the code in an IPython Notebook and then click on File| Download As| Python. Save this file to a directory and run it as we outlined in Chapter 11, Classifying Objects in Images using Deep Learning.

To do this, we will need the os...