Book Description:
 
Handbook of Machine Learning for Computational Optimization: Applications and Case Studies by Vishal Jain, Sapna Juneja, Abhinav Juneja, and Ramani Kannan is a comprehensive resource that delves into the latest advancements in machine learning techniques applied to computational optimization. This edition emphasizes a predictive and futuristic approach, showcasing how machine learning serves as a promising tool for developing sustainable solutions and efficient algorithms across various applications.
 
This book fosters a deeper understanding of topics such as:
Analysis of EMG signals using extreme learning machines with nature-inspired feature selection techniques.
Detection of breast cancer utilizing various machine learning and deep learning algorithms.
Deep learning approaches for traffic sign recognition on embedded systems.
Massive data classification of brain tumors using deep neural networks.
 
It is an invaluable resource for undergraduate and graduate students, researchers, professionals, and application designers seeking to enhance their knowledge in machine learning and its applications in computational optimization.
 
This high-quality PDF eBook is available in an interactive format, making it an essential asset for those aiming to excel in implementing machine learning techniques for optimization problems. Purchase this eBook and save up to 80% at Ebookworm.
 
About the Author(s):
 
Vishal Jain: An Associate Professor in the Department of Computer Science and Engineering at Sharda University, Greater Noida, India. Dr. Jain has authored over 70 research papers and edited more than 10 books with reputed publishers. His research areas include information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, and sensor networks.
 
Sapna Juneja: A Professor at IMS, Ghaziabad, India, with over 16 years of teaching experience. She completed her doctorate and master's in Computer Science and Engineering from M.D. University, Rohtak. Her research focuses on software reliability of embedded systems, with interests in software engineering, computer networks, operating systems, database management systems, and artificial intelligence.
 
Abhinav Juneja: Currently a Professor in the Department of Information Technology at KIET Group of Institutions, Delhi-NCR, Ghaziabad, India. With more than 19 years of teaching experience, he holds a doctorate in Computer Science and Engineering. His research interests include software reliability, IoT, machine learning, and soft computing.
 
Ramani Kannan: A Senior Lecturer at the Center for Smart Grid Energy Research, Institute of Autonomous Systems, Universiti Teknologi PETRONAS (UTP), Malaysia. Dr. Kannan has published over 130 papers in reputed national and international journals and conferences. His expertise includes power electronics and drives, with a focus on machine learning applications in engineering.