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

Disambiguation


Text data is often called an unstructured format. There is a lot of information in text, but it is just there; no headings, no required format (save for normal grammatical rules), loose syntax, and other problems prohibit the easy extraction of information from text. The data is also highly connected, with lots of mentions and cross-references—just not in a format that allows us to easily extract it! Even seemingly easy problems, such as determining if a word is a noun, have lots of weird edge cases that make it difficult to do reliably.

We can compare the information stored in a book with that stored in a large database to see the difference. In the book, there are characters, themes, places, and lots of information. However, a book needs to be read and interpreted, with cultural context, to gain this information. In contrast, a database sits on your server with column names and data types. All the information is there and the level of interpretation needed to extract specific...