Tutorial Based Primer Second Edition Chapman Hallcrc Data Mining And Knowledge

Data mining and knowledge discovery have become essential tools in various industries and academic fields. The Tutorial Based Primer Second Edition Chapman Hallcrc Data Mining And Knowledge book provides a comprehensive guide to understanding the principles and techniques behind these important concepts. Whether you are a beginner or an experienced data professional, this book offers a valuable resource to advance your knowledge and skills in data mining and knowledge discovery.

What is Data Mining?

Data mining is the process of analyzing large datasets to discover patterns, relationships, and valuable insights. It involves using statistical and mathematical techniques to make predictions and uncover hidden patterns within the data. Data mining enables organizations to make informed decisions, improve business operations, and gain a competitive edge in the market.

What is Knowledge Discovery?

Knowledge discovery is the process of extracting useful knowledge from vast amounts of data. It involves combining data mining techniques with domain knowledge to transform raw data into actionable insights. Knowledge discovery encompasses various steps, including data preprocessing, data selection, data transformation, pattern discovery, and knowledge representation.

Data Mining: A Tutorial-Based Primer, Second Edition (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

by Alex Villavasso(2nd Edition, Kindle Edition)

5 out of 5

Language	:	English
File size	:	54687 KB
Screen Reader	:	Supported
Print length	:	529 pages

FREE

About the Tutorial Based Primer Second Edition

The Tutorial Based Primer Second Edition Chapman Hallcrc Data Mining And Knowledge book is a comprehensive guide that provides step-by-step tutorials and real-world examples to help readers understand the fundamental concepts and techniques of data mining and knowledge discovery. It covers a wide range of topics, including data preprocessing, association rule mining, classification, clustering, text mining, and web mining.

Key Features of the Book

• Clear explanations of complex concepts
• Practical examples and case studies
• Step-by-step tutorials for hands-on learning
• Comprehensive coverage of various data mining techniques
• Insights into the latest trends and advancements in the field
• Useful tips and best practices

Who is This Book For?

This book is suitable for individuals who are interested in learning data mining and knowledge discovery. It is a valuable resource for students and professionals in fields such as data science, machine learning, artificial intelligence, business analytics, and information technology. Whether you are a beginner or have some prior knowledge, this book provides a solid foundation for mastering the concepts and techniques of data mining.

The Tutorial Based Primer Second Edition Chapman Hallcrc Data Mining And Knowledge book is a must-have resource for anyone looking to gain a deeper understanding of data mining and knowledge discovery. Its comprehensive coverage, practical examples, and step-by-step tutorials make it an invaluable tool for both beginners and experienced professionals. By leveraging the techniques discussed in this book, individuals and organizations can unlock the potential of their data, make informed decisions, and stay ahead in today's data-driven world.

Are you ready to delve into the fascinating world of data mining and knowledge discovery? Grab your copy of the Tutorial Based Primer Second Edition Chapman Hallcrc Data Mining And Knowledge book today and embark on your journey to becoming a data mining expert!

Data Mining: A Tutorial-Based Primer, Second Edition (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

by Alex Villavasso(2nd Edition, Kindle Edition)

5 out of 5

Language	:	English
File size	:	54687 KB
Screen Reader	:	Supported
Print length	:	529 pages

FREE

Data Mining: A Tutorial-Based Primer, Second Edition provides a comprehensive to data mining with a focus on model building and testing, as well as on interpreting and validating results. The text guides students to understand how data mining can be employed to solve real problems and recognize whether a data mining solution is a feasible alternative for a specific problem. Fundamental data mining strategies, techniques, and evaluation methods are presented and implemented with the help of two well-known software tools.

Several new topics have been added to the second edition including an to Big Data and data analytics, ROC curves, Pareto lift charts, methods for handling large-sized, streaming and imbalanced data, support vector machines, and extended coverage of textual data mining. The second edition contains tutorials for attribute selection, dealing with imbalanced data, outlier analysis, time series analysis, mining textual data, and more.

The text provides in-depth coverage of RapidMiner Studio and Weka’s Explorer interface. Both software tools are used for stepping students through the tutorials depicting the knowledge discovery process. This allows the reader maximum flexibility for their hands-on data mining experience.