Machine Learning Applications
Practical resource on the importance of Machine Learning and Deep Learning applications in various technologies and real-world situations
Machine Learning Applications discusses methodological advancements of machine learning and deep learning, presents applications in image processing, including face and vehicle detection, image classification, object detection, image segmentation, and delivers real-world applications in healthcare to identify diseases and diagnosis, such as creating smart health records and medical imaging diagnosis, and provides real-world examples, case studies, use cases, and techniques to enable the reader's active learning.
Composed of 13 chapters, this book also introduces real-world applications of machine and deep learning in blockchain technology, cyber security, and climate change. An explanation of AI and robotic applications in mechanical design is also discussed, including robot-assisted surgeries, security, and space exploration. The book describes the importance of each subject area and detail why they are so important to us from a societal and human perspective.
Edited by two highly qualified academics and contributed to by established thought leaders in their respective fields, Machine Learning Applications includes information on:
With its practical approach to the subject, Machine Learning Applications is an ideal resource for professionals working with smart technologies such as machine and deep learning, AI, IoT, and other wireless communications; it is also highly suitable for professionals working in robotics, computer vision, cyber security and more.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Indranath Chatterjee is a Professor in the Department of Computer Engineering, at Tongmyong University, South Korea. He received his PhD from University of Delhi, India and has authored several books and numerous, research papers. His areas of research are AI, computer vision, computation neuroscience and medical imaging.
Sheetal Zalte is an Assistant Professor in the Department of Computer Science at Shivaji University, India. She earned her PhD from Shivaji University, India, and has published many research papers. Her research area is mobile adhoc networks.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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