Cantitate/Preț
Produs

Data-Driven Innovation for Intelligent Technology: Studies in Big Data, cartea 148

Editat de Hiram Ponce, Jorge Brieva, Octavio Lozada-Flores, Lourdes Martínez-Villaseñor, Ernesto Moya-Albor
en Limba Engleză Paperback – 17 apr 2025

This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value.
It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others.
This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems.
Citește tot Restrânge

Din seria Studies in Big Data

Preț: 125392 lei

Preț vechi: 156740 lei
-20%

Puncte Express: 1881

Carte tipărită la comandă

Livrare economică 22-28 mai


Specificații

ISBN-13: 9783031542794
ISBN-10: 3031542797
Pagini: 260
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.4 kg
Editura: Springer
Colecția Studies in Big Data
Seria Studies in Big Data


Cuprins

Contactless Video-based Vital-sign Measurement Methods: A Data-driven Review.- Enhancing STEAM in Education 4.0: A Review of Data-driven Technological Improvements.- State-of-the-Art Review in Explainable Machine Learning for Smart-Cities Applications.-  Exploring the Connection Between Digital Systems and Sustainability: Synergy for a Brighter Future.

Textul de pe ultima copertă

This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value.
It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others.
This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems.