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Cover Art
E-RESOURCE
Author Squire, Megan, author.

Title Mastering Data Mining with Python – Find patterns hidden in your data [electronic resource] / Squire, Megan.

Published Packt Publishing, 2016.

Copies

Location Call No. Status
 UniM INTERNET resource    AVAILABLE
Edition 1st edition
Physical description 268 p.
Series Safari Books Online
Summary Learn how to create more powerful data mining applications with this comprehensive Python guide to advance data analytics techniques About This Book Dive deeper into data mining with Python – don’t be complacent, sharpen your skills! From the most common elements of data mining to cutting-edge techniques, we’ve got you covered for any data-related challenge Become a more fluent and confident Python data-analyst, in full control of its extensive range of libraries Who This Book Is For This book is for data scientists who are already familiar with some basic data mining techniques such as SQL and machine learning, and who are comfortable with Python. If you are ready to learn some more advanced techniques in data mining in order to become a data mining expert, this is the book for you! What You Will Learn Explore techniques for finding frequent itemsets and association rules in large data sets Learn identification methods for entity matches across many different types of data Identify the basics of network mining and how to apply it to real-world data sets Discover methods for detecting the sentiment of text and for locating named entities in text Observe multiple techniques for automatically extracting summaries and generating topic models for text See how to use data mining to fix data anomalies and how to use machine learning to identify outliers in a data set In Detail Data mining is an integral part of the data science pipeline. It is the foundation of any successful data-driven strategy – without it, you'll never be able to uncover truly transformative insights. Since data is vital to just about every modern organization, it is worth taking the next step to unlock even greater value and more meaningful understanding. If you already know the fundamentals of data mining with Python, you are now ready to experiment with more interesting, advanced data analytics techniques using Python's easy-to-use interface and extensive range of libraries. In this book, you'll go deeper into many often overlooked areas of data mining, including association rule mining, entity matching, network mining, sentiment analysis, named entity recognition, text summarization, topic modeling, and anomaly detection. For each data mining technique, we'll review the state-of-the-art and current best practices before comparing a wide variety of strategies for solving each problem. We will then implement example solutions using real-world data from the domain of software e...
Reproduction Electronic reproduction. Boston, MA : Safari, Available via World Wide Web.
System notes Mode of access: World Wide Web.
NOTES Copyright © 2016 Packt Publishing
Issuing body notes Made available through: Safari, an O’Reilly Media Company.
Other author Safari, an O’Reilly Media Company.
Subject Electronic books.
ISBN 9781785889950
9781785885914
Standard Number 9781785889950