Mehdi Ghayoumi

eBook, ePUB

Deep Learning in Practice (eBook, ePUB)

Beschreibung

Deep Learning in Practice helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures. It will serve as a useful reference for learning deep learning fundamentals and implementing a deep learning model for any project, step by step.

Technische Details

• Geräte: eReader
• mit Kopierschutz

Barrierefreiheit

• Text-to-Speech
• E-Mail des Verlags für Barrierefreiheitsfragen: [e-mail]
• ARIA-Rollen für verbesserte strukturelle Navigation
• Navigation über vor-/zurück-Elemente ohne Inhaltsverzeichnis
• Seitennummerierung folgt dem gedruckten Werk
• Mathematische Inhalte in MathML für assistive Technologien
• Kurze Alternativtexte für nicht-textuelle Inhalte vorhanden
• Text und Medien in logischer Lesereihenfolge angeordnet
• Navigierbarer Index mit direktem Zugriff auf Indexbegriffe
• Navigierbares Inhaltsverzeichnis für direkten Zugriff auf Text und Medien

Autor

Dr. Mehdi Ghayoumi is a course facilitator at Cornell University and adjunct faculty of Computer Science at the University of San Diego. Prior to this, he was a research assistant professor at SUNY at Binghamton, where he was the Media Core Lab's dynamic leader. He was also a lecturer at Kent State University, where he received the Teaching Award for two consecutive years in 2016 and 2017. In addition, he has been teaching machine learning, data science, robotic and programming courses for several years.

Dr. Ghayoumi research interests are in Machine Learning, Machine Vision, Robotics, and Human-Robot Interaction (HRI). His research focuses are on building real systems for realistic environment settings, and his current projects have applications in Human-Robot Interaction, manufacturing, biometric, and healthcare.

He is a technical program committee member of several conferences, workshops, and editorial board member of several journals in machine learning, mathematics, and robotics, like ICML, ICPR, HRI, FG, WACV, IROS, CIBCB, and JAI. In addition, his research papers have been published at conferences and journals in the fields, including Human-Computer Interaction (HRI), Robotics Science and Systems (RSS), International Conference on Machine Learning and Applications (ICMLA), and others.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 218
• Erscheinungstermin: 30. November 2021
• Englisch
• ISBN-13: 9781000483390
• Artikelnr.: 62733780