Topic: Data Storage & Management

Objective Information Theory (OIT) is proposed to represent and compute the information in a large-scale complex information system with big data in this monograph. To formally analyze, design, develop, and...

This open access book constitutes the revised selected papers of the First International Symposium on AI, Data and Digitalization, SAIDD 2023, held in Sogndal, Norway, during May 9–10, 2023. The...

This open access comprehensive methodological book offers a much-needed answer to the lack of resources and methodological guidance in learning analytics, which has been a problem ever since the field...

Platform Embedded Security Technology Revealed is an in-depth introduction to Intel’s platform embedded solution: the security and management engine. The engine is shipped inside most Intel platforms for servers, personal computers,...

This open access book is a modern guide for all C++ programmers to learn Threading Building Blocks (TBB). Written by TBB and parallel programming experts, this book reflects their collective...

This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand...

This open access book contains eight chapters that deal with database technologies, including the development history of database, database fundamentals, introduction to SQL syntax, classification of SQL syntax, database security...

This open access book presents the mathematical methods for huge data and network analysis. The automotive industry has made steady progress in technological innovations under the names of Connected Autonomous-Shared-Electric...

Beginning and experienced programmers will use this comprehensive guide to persistent memory programming. You will understand how persistent memory brings together several new software/hardware requirements, and offers great promise for...

Using real-world data case studies, this innovative and accessible textbook introduces an actionable framework for conducting trustworthy data science. Most textbooks present data science as a linear analytic process involving...

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results...

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge. Deep learning has revolutionized pattern recognition, introducing...