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

More books from Packt Publishing

Cover of the book Angular 2 Cookbook by Robert Layton
Cover of the book Wireshark Essentials by Robert Layton
Cover of the book Building a BeagleBone Black Super Cluster by Robert Layton
Cover of the book Express Web Application Development by Robert Layton
Cover of the book Mastering Zendesk by Robert Layton
Cover of the book WCF 4.0 Multi-tier Services Development with LINQ to Entities by Robert Layton
Cover of the book Mastering Tableau 2019.1 by Robert Layton
Cover of the book TestNG Beginner's Guide by Robert Layton
Cover of the book The Node Craftsman Book by Robert Layton
Cover of the book WordPress 2.9 E-Commerce by Robert Layton
Cover of the book Data Analysis with R by Robert Layton
Cover of the book Agile Project Management with GreenHopper 6 Blueprints by Robert Layton
Cover of the book Building Virtual Pentesting Labs for Advanced Penetration Testing - Second Edition by Robert Layton
Cover of the book Software-Defined Networking (SDN) with OpenStack by Robert Layton
Cover of the book ServiceNow: Building Powerful Workflows by Robert Layton
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy