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Data Scientists are experts at analyzing, modelling and visualizing data but, at one point or another, have all encountered difficulties in collaborating with or delivering their work to the people and systems that matter.
This book explores the need for a data-centric AI approach and its application in the multidisciplinary domain, compared to a model-centric approach.
Metaphor and Corpus Linguistics: Building and Investigating an English as a Medium of Instruction... Læs mere
Cut the Gordian Knot of the Social Media Data chaos with the power of Graph Databases. Learn how to combine and migrate data from multiple sources to Neo4j.
This book examines the full potential of Digital Twins as a means of creating more sustainable urban habitats. For... Læs mere
One of the most popular database systems, Microsoft SQL Server 2019 Express, is presented and implemented in the book with over 40... Læs mere
This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various... Læs mere
The concept of deep machine learning is easier to understand by paying attention to the cyclic stochastic time series and a time series whose content is non-stationary not only within the cycles, but also over the cycles as the cycle-to-cycle variations.
Pulling aside the curtain of ‘Big Data’ buzz, this book introduces C-suite and other non-technical senior leaders to the essentials of obtaining and maintaining accurate, reliable data, especially for decision-making purposes.
This book cover wireless communication, security issues, advanced wireless sensor networks, routing protocols of WSNs... Læs mere
While most discoverability evaluation studies in the Library and Information Science field discuss the intersection of... Læs mere
This 2010 comprehensive overview of relational mathematics provides an easy introduction to the topic, but is nevertheless theoretically sound and up-to-date. Assuming a minimum... Læs mere