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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition: Practical Machine Learning Tools and Techniques (The Morgan Kaufmann Series in Data Management Systems) by Ian H. Witten  (1)  £23.99

The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling by Ralph Kimball  (6)  £20.79

Introduction to Data Mining by Pang-Ning Tan

Data Mining Techniques, Second Edition: for Market Ing, Sales, and Customer Relationship Management by Michael J. A. Berry  (8)  £22.09

MACHINE LEARNING (Mcgraw-Hill International Edit) by Thom M. Mitchell  (3)  £43.99

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Book Description
Here's the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges. Data Mining: Concepts and Techniques equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery in large corporate databases.

Written expressly for database practitioners and professionals, this book begins with a conceptual introduction designed to get you up to speed. This is followed by a comprehensive and state-of-the-art coverage of data mining concepts and techniques. Each chapter functions as a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. Wherever possible, the authors raise and answer questions of utility, feasibility, optimization, and scalability, keeping your eye on the issues that will affect your project's results and your overall success.

Data Mining: Concepts and Techniques is the master reference that practitioners and researchers have long been seeking. It is also the obvious choice for academic and professional classrooms.

Classroom Features Available Online:
- instructor's manual
- course slides (in PowerPoint)
- course supplementary readings
- sample assignments and course projects

Synopsis
Here's the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges. "Data Mining: Concepts and Techniques" equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery in large corporate databases. Written expressly for database practitioners and professionals, this book begins with a conceptual introduction designed to get you up to speed. This is followed by a comprehensive and state-of-the-art coverage of data mining concepts and techniques. Each chapter functions as a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. Wherever possible, the authors raise and answer questions of utility, feasibility, optimization, and scalability, keeping your eye on the issues that will affect your project's results and your overall success. "Data Mining: Concepts and Techniques" is the master reference that practitioners and researchers have long been seeking. It is also the obvious choice for academic and professional classrooms.

The classroom features that are available online include: instructor's manual - course slides (in PowerPoint) - course supplementary readings - sample assignments and course projects. It offers a comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data. It is organized as a series of stand-alone chapters so you can begin anywhere and immediately apply what you learn. It presents dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects. It provides in-depth, practical coverage of essential data mining topics, including OLAP and data warehousing, data preprocessing, concept description, association rules, classification and prediction, and cluster analysis. It addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields.

First Sentence
This book is an introduction to what come to known as data mining and knowledge spective, where emphasis is placed on basic data mining concepts and techniques for uncovering interesting data patterns hidden in large data sets. Read the first page Browse Sample Pages
Front Cover | Copyright | Table of Contents | Excerpt | Index | Back Cover

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Data Mining: Practical Machine Learning Tools and Techniques, Second Edition: Practical Machine Learning Tools and Techniques (The Morgan Kaufmann Series in Data Management Systems) by Ian H. Witten  (1)  £23.99

Introduction to Data Mining by Pang-Ning Tan

Text Mining: Predictive Methods for Analyzing Unstructured Information by Sholom M. Weiss £42.50

Data Mining Techniques, Second Edition: for Market Ing, Sales, and Customer Relationship Management by Michael J. A. Berry  (8)  £22.09

Principles of Data Mining (Adaptive Computation and Machine Learning) by D Hand  (1)  £39.85

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Most Helpful Customer Reviews   4 of 4 people found the following review helpful: An excellent data mining book, 13 Mar 2004 By A Customer If you are interesting to understand the principles of data mining in large corporate databases, then this book should be your first choice. It presents dozens of algorithms and implementation examples -in pseudocode- . The book takes the reader through the whole processes of knowledge discovery in large database, explaining each process in great details and answering why it needs to be done. The book has a good coverage of data preparation/preprocessing, association rules, classification and prediction, and cluster analysis. If you are looking for a book that covers advance topics in data mining such as time-series databases, text-databases, spatial databases, then, you need to look for another book that covers them in more details. However, this book needs to be in your bookshelf as the basis for understanding data mining in large database. In general, the book is easy to read with many diagrams illustrating the concepts. Also, it provides the reader with the current trend research areas in data mining.  Comment | Permalink | Was this review helpful to you? (Report this)   4 of 4 people found the following review helpful: Very Good, 18 Feb 2004 By  Chris (Europe) - See all my reviews This is a very good book, with thourough explanations Altough I initialy used as a classbook, I still found it useful for researching and application develoment. It doesn't assume any knowledge in this field but still is not boring for people already aware of data mining principles.  Comment | Permalink | Was this review helpful to you? (Report this)