Distributed Systems: Concurrency and Consistency explores the gray area of distributed systems and draws a map of weak consistency criteria, identifying several families and demonstrating how these may be implemented into a programming language. Unlike their sequential counterparts, distributed systems are much more difficult to design, and are therefore prone to problems. On a large scale, usability reminiscent of sequential consistency, which would provide the same global view to all use...

This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Py...

Data Mining Techniques addresses all the major and latest techniques of data mining and data warehousing. It deals in detail with the latest algorithms for discovering association rules, decision trees, clustering, neural networks and genetic algorithms. The book contains the algorithmic details of different techniques such as A priori, Pincer-search, Dynamic Itemset Counting, FP-Tree growth, SLIQ, SPRINT, BOAT, CART, RainForest, BIRCH, CURE, BUBBLE, ROCK, STIRR, PAM, CLARANS, DBSCAN, GSP,...

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using...

Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle—the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don’t need any programming or linguistics experience to get started.Using detailed examples at every step, you’ll learn how the MATTER Annotation Developm...

Information Modeling and Relational Databases, Second Edition, provides an introduction to ORM (Object-Role Modeling)and much more. In fact, it is the only book to go beyond introductory coverage and provide all of the in-depth instruction you need to transform knowledge from domain experts into a sound database design. This book is intended for anyone with a stake in the accuracy and efficacy of databases: systems analysts, information modelers, database designers and administrators, and ...

UML, the Universal Modeling Language, was the first programming language designed to fulfill the requirement for "universality." However, it is a software-specific language, and does not support the needs of engineers designing from the broader systems-based perspective. Therefore, SysML was created. It has been steadily gaining popularity, and many companies, especially in the heavily-regulated Defense, Automotive, Aerospace, Medical Device and Telecomms industries, are already using SysM...

Cryptography has been employed in war and diplomacy from the time of Julius Caesar. In our Internet age, cryptography's most widespread application may be for commerce, from protecting the security of electronic transfers to guarding communication from industrial espionage. This accessible introduction for undergraduates explains the cryptographic protocols for achieving privacy of communication and the use of digital signatures for certifying the validity, integrity, and origin of a messa...

This book discusses how model-based approaches can improve the daily practice of software professionals. This is known as Model-Driven Software Engineering (MDSE) or, simply, Model-Driven Engineering (MDE).MDSE practices have proved to increase efficiency and effectiveness in software development, as demonstrated by various quantitative and qualitative studies. MDSE adoption in the software industry is foreseen to grow exponentially in the near future, e.g., due to the convergence ...

Foreword by Mark Stephen LaRow, Vice President of Products, MicroStrategy"A unique and authoritative book that blends recent research developments with industry-level practices for researchers, students, and industry practitioners." Il-Yeol Song, Professor, College of Information Science and Technology, Drexel University

Software practitioners are rapidly discovering the immense value of Domain-Specific Languages (DSLs) in solving problems within clearly definable problem domains. Developers are applying DSLs to improve productivity and quality in a wide range of areas, such as finance, combat simulation, macro scripting, image generation, and more. But until now, there have been few practical resources that explain how DSLs work and how to construct them for optimal use.***Software Language Engine...

This extensively classroom-tested text takes an innovative approach to explaining software testing that defines it as the process of applying a few precise, general-purpose criteria to a structure or model of the software. The book incorporates cutting-edge developments, including techniques to test modern types of software such as OO, web applications, and embedded software. This revised second edition significantly expands coverage of the basics, thoroughly discussing test automaton fram...