Data mining

This Element highlights the archaeology of methods developed in chemometrics, artificial intelligence, and Bayesian statistics.

Know-how für erfolgreiche Self-Service-Initiativen- Praktischer Leitfaden zur unternehmensweiten Einführung von Self-Service- Fokus auf die Konzeption und Governance von Self-Service- Mit Impulsen, was bei einer laufenden Self-Service-Organisation zu beachten istSelf-Service im BI- und Analytics-Kontext bedeutet, dass BI-Anwender selbst aktiv werden, um auf bestimmte Daten und Informationsprodukte zuzugreifen.

A comprehensive guide to machine learning and statistics for students and researchers of environmental data science.

The shifting focus of service from the 1980s to 2000shas proved that IT not only lowers the cost of servicebut creates avenues to enhance and increase revenuethrough service.

Volume II of this series discusses the technology used to implement a big data analysis capability within a service-oriented organization.

This volume will assist readers in fitting big data analysis into their service-based organizations.

A practical guide for data scientists who want to improve the performance of any machine learning solution with feature engineering.

Know-how für erfolgreiche Self-Service-Initiativen- Praktischer Leitfaden zur unternehmensweiten Einführung von Self-Service- Fokus auf die Konzeption und Governance von Self-Service- Mit Impulsen, was bei einer laufenden Self-Service-Organisation zu beachten istSelf-Service im BI- und Analytics-Kontext bedeutet, dass BI-Anwender selbst aktiv werden, um auf bestimmte Daten und Informationsprodukte zuzugreifen.

Business-Intelligence-Lösungen sind für Unternehmen unabdingbar, um Datenmengen in vertretbarer Zeit zu analysieren und daraus resultierend Entscheidungen zu treffen.

Business-Intelligence-Lösungen sind für Unternehmen unabdingbar, um Datenmengen in vertretbarer Zeit zu analysieren und daraus resultierend Entscheidungen zu treffen.

The migration of data is an important process when introducing SAP systems or adopting new data from third-party systems.

Volume II of this series discusses the technology used to implement a big data analysis capability within a service-oriented organization.

This volume will assist readers in fitting big data analysis into their service-based organizations.

Data is constantly increasing and data analysts are in higher demand than ever.

Data is constantly increasing and data analysts are in higher demand than ever.

The shifting focus of service from the 1980s to 2000shas proved that IT not only lowers the cost of servicebut creates avenues to enhance and increase revenuethrough service.

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

This book describes techniques and results in cyber threat intelligence from the center of the malicious hacking underworld - the dark web.

Introductory, theory-practice balanced text teaching the fundamentals of databases to advanced undergraduates or graduate students in information systems or computer science.

This book describes techniques and results in cyber threat intelligence from the center of the malicious hacking underworld - the dark web.

A hands-on, entry-level guide to algorithms for extracting information about social and economic behavior from network data.

A hands-on, entry-level guide to algorithms for extracting information about social and economic behavior from network data.

An authoritative and in-depth treatment of state space methods, with a range of applications in neural and clinical data.

An authoritative and in-depth treatment of state space methods, with a range of applications in neural and clinical data.

A resource for social scientists on how Twitter data can be used to study individual behavior and social interaction.

Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Data access is essential for serving the public good.

Data access is essential for serving the public good.

Integrates social media, social network analysis, and data mining to provide an understanding of the potentials of social media mining.

Covers text mining and link detection algorithms, pre-processing techniques, knowledge representation, visualization and applications.

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

A technical guide to performing systematic experiments that create more transparency for corporate surveillance and its algorithms.

Now in paperback and fortified with exercises, this brilliant, enjoyable text demystifies data science, statistics and machine learning.

Overviews of interdisciplinary research partnerships applying AI, IE, and OR to societal and operational problems in healthcare settings.

Cutting-edge models for proactive cybersecurity, applying AI, learning, and network analysis to information mined from hacker communities.

Cutting-edge models for proactive cybersecurity, applying AI, learning, and network analysis to information mined from hacker communities.

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.

An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.

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.

An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.

This is the first comprehensive overview of the exciting field of the ''science of science''.

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