Innovations in Machine and Deep Learning: Case Studies and Applications: Studies in Big Data, cartea 134
Editat de Gilberto Rivera, Alejandro Rosete, Bernabé Dorronsoro, Nelson Rangel-Valdezen Limba Engleză Hardback – 29 sep 2023
The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0.
This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.
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Specificații
ISBN-13: 9783031406874
ISBN-10: 3031406877
Pagini: 514
Ilustrații: IX, 514 p. 196 illus., 159 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Studies in Big Data
Locul publicării:Cham, Switzerland
ISBN-10: 3031406877
Pagini: 514
Ilustrații: IX, 514 p. 196 illus., 159 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Studies in Big Data
Locul publicării:Cham, Switzerland
Cuprins
Notă biografică
Textul de pe ultima copertă
In recent years, significant progress has been made in achieving artificial intelligence (AI) with an impact on students, managers, scientists, health personnel, technical roles, investors, teachers, and leaders. This book presents numerous successful applications of AI in various contexts.
The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0.
This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.
The innovative implications covered fall under the general field of machine learning (ML), including deep learning, decision-making, forecasting, pattern recognition, information retrieval, and interpretable AI. Decision-makers and entrepreneurs will find numerous successful applications in health care, sustainability, risk management, human activity recognition, logistics, and Industry 4.0.
This book is an essential resource for anyone interested in challenges, opportunities, and the latest developments and real-world applications of ML. Whether you are a student, researcher, practitioner, or simply curious about AI, this book provides valuable insights and inspiration for your work and learning.
Caracteristici
Introduces machine and deep learning approaches for solving challenging problems Collects the latest technological innovations and models related to deep learning Includes representative applications and case studies using cutting-edge technologies