The Handbook of Data Science and AI: Generate Value from Data with Machine Learning and Data Analytics
by Stefan Papp, Wolfgang Weidinger, Katherine Munro, Bernhard Ortner, Annalisa Cadonna, Georg Langs, Roxane Licandro, Mario Meir-Huber, Danko Nikolić, Zoltan Toth, Barbora Vesela, Rania Wazir, Günther Zauner
The Handbook of Data Science and AI presents a broad exploration of data science, artificial intelligence, machine learning, and data analytics. Written by a large group of contributors, it examines how these fields connect and how organizations can use data-driven approaches to generate value.
About This Book
The Handbook of Data Science and AI explores how organizations can generate value from data through data science, artificial intelligence, machine learning, and data analytics.
Its subject is presented across interconnected areas, making the book a broad reference for readers seeking an overview of modern data-focused technologies and practices.
The handbook brings together contributions from a diverse group of authors, reflecting multiple perspectives on data science and AI.
Suitable as a reference for readers interested in the foundations, applications, and value potential of data-driven work.
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