Data mining

Cluster or co-cluster analyses are important tools in a variety of scientific areas.

Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools.

This book provides a detailed and up-to-date overview on classification and data mining methods.

This book provides a detailed and up-to-date overview on classification and data mining methods.

Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools.

A visual approach to data mining.

A visual approach to data mining.

Praise for the First Edition .

Praise for the First Edition .

Provides readers with the methods, algorithms, and means to perform text mining tasks This book is devoted to the fundamentals of text mining using Perl, an open-source programming tool that is freely available via the Internet (www.

Focuses on insights, approaches, and techniques that are essential to designing interactive graphics and visualizations Making Sense of Data III: A Practical Guide to Designing Interactive Data Visualizations explores a diverse range of disciplines to explain how meaning from graphical representations is extracted.

Focuses on insights, approaches, and techniques that are essential to designing interactive graphics and visualizations Making Sense of Data III: A Practical Guide to Designing Interactive Data Visualizations explores a diverse range of disciplines to explain how meaning from graphical representations is extracted.

The leading introductory book on data mining, fully updated and revised!

The leading introductory book on data mining, fully updated and revised!

Understand how to use the new features of Microsoft SQL Server 2008 for data mining by using the tools in Data Mining with Microsoft SQL Server 2008, which will show you how to use the SQL Server Data Mining Toolset with Office 2007 to mine and analyze data.

In the big data age, this Element offers many modern methods and opensource code for learning from high dimensional data.

A practical guide to text analysis with Python: the intuition, the math, the code.

Offers researchers and teachers an introduction to clustering, with R code and real data to facilitate interaction with the concepts.

Techniques for interpreting commonly used discrete choice models, illustrated with extensive examples including replication code and data.

Techniques for interpreting commonly used discrete choice models, illustrated with extensive examples including replication code and data.

This Element explains the statistical foundations of computerized adaptive inventories and how to use the tools provided to implement them.

This Element explains the statistical foundations of computerized adaptive inventories and how to use the tools provided to implement them.

Explores the critical role time plays in our understanding of causality, across psychology, biology, physics and the social sciences.

Explores the critical role time plays in our understanding of causality, across psychology, biology, physics and the social sciences.

New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

This practical guide for students, researchers and practitioners offers real world guidance for data-driven decision making and innovation.

This practical guide for students, researchers and practitioners offers real world guidance for data-driven decision making and innovation.

Looks at the use of Twitter as a data source.

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

This snapshot of the frontier of statistics and network analysis focuses on the foundational topics of modeling, sampling, and design.

This compact account covers both well-established methodology and the theory of models recently introduced in the graphical model literature.

This book teaches fundamentals of stream processing, covering application design, distributed systems infrastructure, and continuous analytic algorithms.

This book teaches fundamentals of stream processing, covering application design, distributed systems infrastructure, and continuous analytic algorithms.

Although change is constant in business and analytics, some fundamental principles and lessons learned are truly timeless, extending and surviving beyond the rapid ongoing evolution of tools, techniques, and technologies.

Life scientists today urgently need training in bioinformatics skills.

Life scientists today urgently need training in bioinformatics skills.

Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine.

Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine.

Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed.

Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed.

Do your product dashboards look funky?

Do your product dashboards look funky?

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice.

Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice.

This practical book provides a comprehensive overview of troubleshooting and performance tuning best practices for Microsoft SQL Server.

This practical book provides a comprehensive overview of troubleshooting and performance tuning best practices for Microsoft SQL Server.

Why is Google Analytics 4 the most modern data model available for digital marketing analytics?

Why is Google Analytics 4 the most modern data model available for digital marketing analytics?

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python.