This book is Part I of the fourth edition of Robert Sedgewick and Kevin Wayne's Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part I contains Chapters 1 through 3 of the book. The fourth edition of Algorithms surveys the most important computer more » algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing - including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. « less
This book is Part II of the fourth edition of Robert Sedgewick and Kevin Wayne's Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part II contains Chapters 4 through 6 of the book. The fourth edition of Algorithms surveys the most important computer more » algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing - including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. « less
Methods and Algorithms
A unified, coherent treatment of current classifier ensemble methods, from fundamentals of pattern recognition to ensemble feature selection, now in its second edition
The art and science of combining pattern classifiers has flourished into a prolific discipline since the first edition of Combining more » Pattern Classifiers was published in 2004. Dr. Kuncheva has plucked from the rich landscape of recent classifier ensemble literature the topics, methods, and algorithms that will guide the reader toward a deeper understanding of the fundamentals, design, and applications of classifier ensemble methods. « less
Bringing classic computing approaches to the Web
Too much work and too little time? If this is daily life for your team, you need kanban, a lean knowledge-management method designed to involve all team members in continuous improvement of your process.
Kanban in Action is a practical introduction to kanban. Written by two kanban coaches who have taught more » the method to dozens of teams, the book covers techniques for planning and forecasting, establishing meaningful metrics, visualizing queues and bottlenecks, and constructing and using a kanban board. « less
The Mikado Method presents a pragmatic process to plan and perform nontrivial technical improvements on an existing software system. The book helps you practice a step-by-step system for identifying the scope and nature of your technical debt, mapping the key dependencies, and determining a safe way more » to approach the "Mikado"âyour goal. A natural by-product of this process is the Mikado Graph, a roadmap that reflects deep understanding of how your system works.
This book builds on agile processes such as refactoring, TDD, and rapid feedback. It requires no special hardware or software and can be practiced by both small and large teams. « less
Getting from Policy to Code to QA to Value
The Privacy Engineer's Manifesto: Getting from Policy to Code to QA to Value is the first book of its kind, offering industry-proven solutions that go beyond mere theory and adding lucid perspectives on the challenges and opportunities raised with the emerging "personal" information economy.
The authors, more » a uniquely skilled team of longtime industry experts, detail how you can build privacy into products, processes, applications, and systems. The book offers insight on translating the guiding light of OECD Privacy Guidelines, the Fair Information Practice Principles (FIPPs), Generally Accepted Privacy Principles (GAPP) and Privacy by Design (PbD) into concrete concepts that organizations, software/hardware engineers, and system administrators/owners can understand and apply throughout the product or process life cycle - regardless of development methodology - from inception to retirement, including data deletion and destruction. « less
A Problem - Solution Approach
Big Data Application Architecture Pattern Recipes provides an insight into heterogeneous infrastructures, databases, and visualization and analytics tools used for realizing the architectures of big data solutions. Its problem-solution approach helps in selecting the right architecture to solve the problem more » at hand. In the process of reading through these problems, you will learn harness the power of new big data opportunities which various enterprises use to attain real-time profits. « less
Introducing Control Theory to Enterprise Programmers
How can you take advantage of feedback control for enterprise programming? With this book, author Philipp K. Janert demonstrates how the same principles that govern cruise control in your car also apply to data center management and other enterprise systems. Through case studies and hands-on simulations, more » you'll learn methods to solve several control issues, including mechanisms to spin up more servers automatically when web traffic spikes.
Feedback is ideal for controlling large, complex systems, but its use in software engineering raises unique issues. This book provides basic theory and lots of practical advice for programmers with no previous background in feedback control. « less
The Affective Computing domain, term coined by Rosalind Picard in 1997, gathers several scientific areas such as computer science, cognitive science, psychology, design and art. The humane-machine interaction systems are no longer solely fast and efficient. They aim to offer to users affective experiences: more » user's affective state is detected and considered within the interaction; the system displays affective state; it can reason about their implication to achieve a task or resolve a problem. In this book, we have chosen to cover various domains of research in emotion-oriented systems. Our aim is also to highlight the importance to base the computational model on theoretical foundations and on natural data. « less