Promotions - Choice's Outstanding Academic Titles 2022 -

A major problem for college graduates is learning to use classroom-earned knowledge to solve real-world problems. Kaliraj and Devi (both, Bharathiar Univ., Tamil Nadu, India) elegantly tackle this problem by integrating chapters on data science use cases from industry, education, and medicine with foundational chapters on deeply technical topics and toolsets including, for example, PySpark, robust statistical procedures, and text analytics methods. The applied chapters form the heart of the book and include quick lists of several real-world applications. These chapters are likely to inspire readers' imaginations toward thinking of new and exciting uses for data science. Chapters on such technical topics as text analytics and robust statistics focus on the technical history and common algorithms before shifting to their application in manipulating data sets from social media, health care records, and e-mail spam use cases. Chapter 15 on implementing a data lake covers the architecture of big data, explaining the storage and accession of data--a good foundation for the use cases in the rest of the book. Readers will become more adept at considering a broad range of data science methods, techniques, and use cases. Student readers will move from the classroom to the workplace with greater confidence. This book is appropriate for use in undergraduate courses.Summing Up: Highly recommended. Lower- and upper-division undergraduates. Professionals. Students in two-year technical programs. General readers.

It will be hard to find a more pivotal convergence of digital technologies than in the book under review. Although many publications focus on blockchain, cryptocurrencies, data integrity consensus algorithms, and smart contracts, this book goes a step beyond. Several chapters discuss the synergy between artificial intelligence (AI) and hyperledger-based frameworks. AI and blockchain might converge in numerous applications, such as financial services, fraud detection, supply chain monitoring, and medical records management. One critical technology presented in several chapters is blockchain databases, which introduce a new transaction model and new approaches to asset storage, metadata, and support for big data volumes. System developers are in the early stages of addressing blockchain limitations resulting from the absence of relational structure and issues with making blockchain queryable. A few chapters cover the increasingly important area of blockchain-related visualizations. Technologies discussed include cryptocurrency visualization systems--peer, security-related, and flow visualizations. One of the more interesting chapters focuses on blockchain creation using Javascript. Some chapters address business and social media applications, such as the excellent chapter on Synapse AI and the changing economic model of using and contributing data. Clearly this book is technical in focus. However, many concepts are introduced in an approachable way for readers new to blockchain and AI.Summing Up: Highly recommended. All readers.

Software architect Bowman offers a general primer on broad swaths of computer science that sheds light on the deep inner workings of the computers people interact with every day. Beginning with a fascinating history of computing, the narrative winds through subjects that "build" the modern computer, component by component, from hardware and networking to operating systems and software. In the technical sections of the book, readers are offered real-life illustrations of architecture diagrams, operating system functions, and even programming codes/methods. These illustrations can help readers understand technical concepts they never understood before at a deep level. Bowman avoids long, monotonous, technical descriptions by interpolating historical time lines and highly relevant applied examples throughout. The final chapter offers details on security and privacy and an important section that answers readers' likely question: how can I protect myself from hacking exploits? This book could be instructive for all who depend on computers to do their jobs and are curious about how the devices work on more-technical levels. Undergraduate students and those working in IT or tech fields who have deeply specialized knowledge but would like to explore areas with which they are unfamiliar will prize this book.Summing Up: Highly recommended. Lower-division undergraduates. Students in two-year technical programs. General readers.

Visual data analysis is a fundamental topic in modern computer science and beyond. The last decade brought exponential growth in data volume and progress in machine learning and data mining. To cope with big data, data analysis methods had to evolve. The addition of interactivity enables iterative analysis and incremental comprehension, two fundamental aspects of human comprehension. Tominski and Schumann (both, Univ. of Rostock) offer a thorough introduction to the field and a wealth of information essential for students, with enough depth to appeal to practitioners and researchers. Chapter 1 begins with basic principles (e.g., visualization as a "method of computing," the "Five W's of Interactive Data Analysis,") but soon delves into current visualization methods and techniques (code for a graph of 77 nodes and 254 edges with their attributes, followed by different visual renderings). Subsequent chapters explain the fundamentals of interactivity and the methods that use it; provide examples of automatic analysis to simplify, focus, group, or transform complex data sets; and explore more-advanced concepts for interactive data learning and multi-display presentations. Abundant visual examples complement the text perfectly. Although the field is rapidly advancing, this book will remain a useful reference for many years to come.Summing Up: Highly recommended. Lower- and upper-division undergraduates. Graduate students, faculty, and professionals.

The introduction of object-oriented programming was a pivotal moment in software engineering, leading to a new way of creating systems by modelling their constituents independently and linking them through shared interfaces. Object orientation allows for the creation of more complex systems, better focus on a small subset of components at any given time, and a greater level of component independence; it even facilitates the creation of software product lines. Designing a system using object orientation requires the mastery of several interdependent concepts, such as abstraction, inheritance, composition, and polymorphism. Dingle (Seattle Univ.) provides a cohesive framework for learning object-oriented design from a practical point of view. Concepts are introduced hierarchically, starting from the idea of encapsulation and design as a contract and drilling down to specifics such as virtual function tables and abstract classes. This approach results in an incremental experience of learning object-oriented design that is rarely found in computer science courses, but that is essential for software engineers who wish to harness the power of object-oriented programming languages in practice. Although no book can fully replace hands-on bench experience, this compact guide can ensure that one's practical efforts will be optimally targeted.Summing Up: Highly recommended. Lower- and upper-division undergraduates. Professionals. Students in two-year technical programs.

What value do maps have in the age of ubiquitous geographic information delivered digitally on mobile devices? Bruce (emer., Univ. of Illinois Urbana-Champaign) directly addresses this question in eight conceptual chapters highlighting the importance of maps for developing thinking and learning in a variety of educational contexts. A computer scientist who taught in the UIUC Department of Information Science, Bruce demonstrates breadth of knowledge in teaching and learning through brief snapshots focused on educational applications of, e.g., maps, globes, global positioning system (GPS) technologies, and the freely available OpenStreetMap database. Although the examples presented include several familiar to most geographers, including Dr. John Snow's London well (cholera spread) and geologist William Smith's strata (biozones), Bruce also includes several unique illustrations of map use, e.g., Parisian street signs, humanitarian aid mapping in Nepal. He adopts a primarily theoretical perspective on maps as used for understanding the world, influenced by distinguished historical educators (Lucy Sprague Mitchell and John Dewey). Each chapter includes multiple illustrations of maps used as "thinking tools," reinforcing the general importance of spatial thinking alongside literacy and numeracy. Although brief, this text provides important insights for general readers and will also be welcomed by geographers, spatial humanities educators, and practitioners working in social studies, science, and early childhood education.Summing Up: Highly recommended. Lower- and upper-division undergraduates. Graduate students, faculty, and professionals. General readers.