Data mining

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

An introductory textbook offering a low barrier entry to data science; the hands-on approach will appeal to students from a range of disciplines.

This book addresses common questions from HCI researchers when trying to do statistical analysis on their data.

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

Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.

A bold retooling of statistics to focus directly on predictive performance with traditional and contemporary data types and methodologies.

This book addresses common questions from HCI researchers when trying to do statistical analysis on their data.

A bold retooling of statistics to focus directly on predictive performance with traditional and contemporary data types and methodologies.

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

Provides a comprehensive textbook covering theory and practical examples for a course on data mining and data warehousing.

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

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

Shows how traditional and nontraditional methods such as anomaly detection and time series can be extended using data analytics.

This book explains the role of big data and statistical physics in understanding macroeconomic concepts.

This book describes the analysis of macroeconomic agent based models using the tools of statistical mechanics.

The first introductory textbook on description logics, relevant to computer science, knowledge representation and the semantic web.

The first introductory textbook on description logics, relevant to computer science, knowledge representation and the semantic web.

Provides a summary of the key developments of a decade of research into the area of data exchange.

Provides a summary of the key developments of a decade of research into the area of data exchange.

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.

This book surveys the myriad facets of monitoring people in motion, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis.

This book surveys the myriad facets of monitoring people in motion, from spatio-temporal data modeling, to data aggregation and warehousing, to data analysis.

Master the process of building MASS models with real examples and hands-on practice.

Guide to key tools for large-scale gene-sequence and annotation comparisons for bioinformatics students and researchers.

A companion to Biological Sequence Analysis (Cambridge, 1998), providing solutions to the original problems and additional worked examples.

Focuses on a few of the important clustering algorithms in the context of information retrieval.