Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems - Softcover

Softcover

ISBN 13: 9798369345689

Verlag: IGI Global, 2024

Inhaltsangabe

The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A resource that encourages interdisciplinary collaboration is needed to bridge the gap between these respected leaders of their own fields. Deep Learning, Reinforcement Learning, and the Rise of Intelligent Systems represents an exploration of the forefront of artificial intelligence, navigating the complexities of this field and its many applications. This guide expertly navigates through the intricate domains of deep learning and reinforcement learning, offering an in-depth journey through foundational principles, advanced methodologies, and cutting-edge algorithms shaping the trajectory of intelligent systems. The book covers an introduction to artificial intelligence and its subfields, foundational aspects of deep learning, a demystification of the architecture of neural networks, the mechanics of backpropagation, and the intricacies of critical elements such as activation and loss functions. The book serves as a valuable educational resource for professionals. Its structured approach makes it an ideal reference for students, researchers, and industry professionals.

Über diesen Titel

Über die Autorinnen und Autoren

Irfan Uddin is currently working as a faculty member at the Institute of Computing, Kohat University of Science and Technology, Kohat, Pakistan. He has received his academic qualifications in computer science and has worked as a researcher on funded projects. He is involved in teaching and research activities related to different diverse computer science topics and has more than eighteen years of teaching plus research experience. He is a member of IEEE, ACM, and HiPEAC. He has actively organized national and international seminars, workshops, and conferences. He has published over a hundred research papers in international journals and conferences. His research interests include machine learning, data science, artificial neural networks, deep learning, convolutional neural networks, recurrent neural networks, attention models, reinforcement learning, generative adversarial networks, computer vision, image processing, machine translation, natural language processing, speech recognition, big data analytics, parallel programming, Multi-core, Many-core and GPUs.

Wali Khan Mashwani received an M.Sc. degree in mathematics from the University of Peshawar, Khyber Pakhtunkhwa, Pakistan, in 1996, and a Ph.D. degree in mathematics from the University of Essex, U.K., in 2012. He is currently a Full Professor of mathematics and the Director of the Institute of Numerical Sciences, Kohat University of Science and Technology (KUST), Khyber Pakhtunkhwa. He is also the Dean of the Physical and Numerical Sciences faculty at KUST. He has published more than 100 academic papers in peer-reviewed international journals and conference proceedings. His research interests include evolutionary computation, hybrid evolutionary multi-objective algorithms, decomposition-based evolutionary methods for multi-objective optimization, mathematical programming, numerical analysis, and artificial neural networks.

Details zur Ausgabe

• Verlag: IGI Global
• Erscheinungsdatum: 2024
• Sprache: Englisch
• ISBN 13: 9798369345689
• Einband: Taschenbuch
• Anzahl der Seiten: 312
• Herausgeber: Uddin M. Irfan, Mashwani Wali Khan
• Kontakt zum Hersteller: preigu GmbH & Co. KG; mail@preigu.de; ; Lengericher Landstr. 19; Osnabrück; Niedersachsen; 49078; Deutschland