This book teaches algorithms that have been used in practice to solve key problems in data mining and includes exercises suitable for students from the advanced undergraduate level and beyond.

The book thoroughly acquaints you with the new generation of data mining tools and techniques and shows you how to use them to make better business decisions.

The basic premise of this book is that it can serve as the basis for a wide range of courses that discuss numerical methods used in data analysis and science.

This book introduces advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.

This book provides a brief, understandable, user-friendly guide to all aspects of Data Science. It also addresses the various skills required.

How to create an environment for exploring data, using lightweight tools such as Ruby, Python, Apache Pig, and the D3.js (Data-Driven Documents) JavaScript library.

This book aims to help data miners, researchers, scholars, and students who wish to apply data mining techniques.

This book presents fundamental concepts and algorithms for those learning data mining for the first time.

This book is for enthusiasts of data warehousing who have limited exposure to databases and would like to learn data warehousing concepts end-to-end.

This tutorial manual provides a comprehensive introduction to R, an open source software package for statistical computing and graphics.

An introduction to Python, together with NumPy, SciPy, and matplotlib for numerical and statistical analaysis, for Econometrics, Statistics and Data Analysis.

In this book, a selection of frequently required statistical tools will be introduced and illustrated.

This book targets to help data miners who wish to apply different data mining techniques, including statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, etc.

In this free book, the three defining characteristics of Big Data - volume, variety, and velocity, are discussed.

This free book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning.

Provides an efficient, user-friendly 'brief' on the current status of Big Data analytics and how you can economically deploy this technology to increase your firm's profitability.

This book is intended to be a useful resource for anyone who thinks that they might be interested in becoming a data journalist, or dabbling in data journalism.

This book represents the full spectrum of data-related content we’ve published on O’Reilly Radar over the last year.

This book is a complete and comprehensive handbook for the application of data mining techniques in marketing and customer relationship management.

This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics.

The book covers the data storage system, computational approaches to biological problems, an introduction to workflow systems, data mining, data visualization, and tips for tailoring existing data analysis software to individual research needs.

The primary difference between a computer science approach and the Informatics approach taken in this book is a greater focus on using Python to solve problems.

This book thoroughly acquaints you with the new generation of data mining tools and techniques and shows you how to use them to make better business decisions.

This book presents the first broad look at the rapidly emerging field of data-intensive science, with the goal of influencing the worldwide scientific and computing research communities and inspiring the next generation of scientists.

Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, etc..

This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social Networks..

This book describes some of the technical methods and systems used for document processing of text and graphics images.

This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data.

This book is an excellent starting point for information professionals to gain a basic understanding of fundamental concepts of metadata.

This book intends to bring together the most recent advances and applications of data mining research in the promising areas of medicine and biology from around the world.

This book goes into the different uses of Data Mining, with Multi-Relational Data Mining (MRDM), the approach to Structured Data Mining, as the main subject of this book..

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