Learning Data Mining with Python

Nonfiction, Computers, Database Management, Data Processing, Application Software, Business Software
Cover of the book Learning Data Mining with Python by Robert Layton, Packt Publishing
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Author: Robert Layton ISBN: 9781784391201
Publisher: Packt Publishing Publication: July 29, 2015
Imprint: Packt Publishing Language: English
Author: Robert Layton
ISBN: 9781784391201
Publisher: Packt Publishing
Publication: July 29, 2015
Imprint: Packt Publishing
Language: English

The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis.

This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems.

There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK.

Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis.

This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems.

There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK.

Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations.

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