Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical an...

In November 2008, John Hattie's ground-breaking book Visible Learning synthesised the results of more than fifteen years research involving millions of students and represented the biggest ever collection of evidence-based research into what actually works in schools to improve learning. Visible Learning for Teachers takes the next step and brings those ground breaking concepts to a completely new audience. Written for students, pre-service and in-service teachers, it explains how to apply th...

A completely updated and expanded comprehensive treatment of VHDL and its applications to the design and simulation of real, industry-standard circuits.

This comprehensive treatment of VHDL and its applications to the design and simulation of real, industry-standard circuits has been completely updated and expanded for the third edition. New features include all VHDL-2008 constructs, an extensive review of digital circuits, RTL analysis, and an unequaled collection of VHDL examples and exerci...

An introduction to the modeling of business information systems, with processes formally modeled using Petri nets. This comprehensive introduction to modeling business-information systems focuses on business processes. It describes and demonstrates the formal modeling of processes in terms of Petri nets, using a well-established theory for capturing and analyzing models with concurrency. The precise semantics of this formal method offers a distinct advantage for modeling processes over the in...

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms. It also describes several key aspects of the application of these al...

Public economics studies how government taxing and spending activities affect the economy―economic efficiency and the distribution of income and wealth. This comprehensive text on public economics covers the core topics of market failure and taxation as well as recent developments in both policy and the academic literature. It is unique not only in its broad scope but in its balance between public finance and public choice and its combination of theory and relevant empirical evidence.

The b...

A comprehensive introduction to using the tools and techniques of neuroscience to understand how consumers make decisions about purchasing goods and services. Contrary to the assumptions of economists, consumers are not always rational actors who make decisions in their own best interests. The new field of behavioral economics draws on the insights of psychology to study non-rational decision making. The newer field of consumer neuroscience draws on the findings, tools, and techniques of neur...

An impassioned look at games and game design that offers the most ambitious framework for understanding them to date.

A comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics.

Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algor...