Introduction to Machine Learning with Security

Theory and Practice Using Python in the Cloud
2. Auflage 2025
ISBN: 978-3-031-59169-3
Verlag: Springer Nature Switzerland

Buch, Englisch, 492 Seiten, Format (B × H): 173 mm x 246 mm, Gewicht: 1144 g

Reihe: Synthesis Lectures on Engineering, Science, and Technology

This book provides an introduction to machine learning, security and cloud computing, from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.  

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Gupta, Pramod

Acken, John M.

Sehgal, Naresh Kumar

Fachgebiete

• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Ambient Intelligence, RFID, Internet der Dinge
• Mathematik | Informatik EDV | Informatik Angewandte Informatik

Inhaltsverzeichnis

Introduction to Machine Learning.- Foundations of Machine Learning.- Deep Learning and cloud computing.- Cloud Computing Concepts.- Practical Aspects in Machine Learning.- Artificial Intelligence and Information Security.- Examples of Analytics in the Cloud.- A case study of Data Collection and Analytics in the Cloud.- Future trends in Hardware based AI and ML.

Über Autor(innen)

Pramod Gupta has more than 20 years of experience as a researcher and academician in various organizations including work with NASA, GE, VISA, and University of California and startups. He has a PhD from McMaster University in Electrical and Computer Engineering with specialization in Neuro-Control of Robotic Manipulators.  He has more than 40 publications on these subjects. His research areas include Neural Networks, Machine Learning, Artificial Intelligence, Data Modeling and Analytics and Data mining.  Presently, he is an Adjunct Faculty and working as an independent data science consultant. 

Naresh K. Sehgal is a CTO at the Deeply Human AI. Before that he worked at NovaSignal for 3 years and at Intel for 31 years in various Engineering and Management roles. Naresh has earned his B.E. from Punjab Engineering College, M.S. and Ph.D. from Syracuse University. He also taught a Cloud Computing class at Santa Clara University, where he earned an MBA.

John M. Acken is a research faculty member in the Electrical and Computer Engineering Department, Portland State University, Portland, OR.  John received his BS and MS in Electrical Engineering from Oklahoma State University and Ph. D. in Electrical Engineering from Stanford University. His projects include technology and devices for information security and identity authentication. John has worked as an Electrical Engineer and Manager at several companies, including the US Army, Sandia National Labs in Albuquerque, New Mexico and Intel in Santa Clara, CA.  John’s time in the US Army was in the Army Security Agency, a branch of NSA during the Vietnam War.