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

Beating CAPTCHAs with Neural Networks


You may find the following topics interesting as well:

Better (worse?) CAPTCHAs

URL: http://scikit-image.org/docs/dev/auto_examples/applications/plot_geometric.html

Larger exercise!

The CAPTCHAs we beat in this example were not as complex as those normally used today. You can create more complex variants using a number of techniques as follows:

Deeper networks

These techniques will probably fool our current implementation, so improvements will need to be made to make the method better. Try some of the deeper networks we used. Larger networks need more data, though, so you will probably need to generate more than the few thousand samples we did here in order to get good performance. Generating these datasets...