Springer Welding and Cutting Case Studies with Supervised Machine Learning: 1 (Engineering Applications of Computational Methods, 1)

This book presents machine learning as a set of pre-requisites, co-requisites, and post-requisites, focusing on mathematical concepts and engineering applications in advanced welding and cutting processes. It describes a number of advanced welding and cutting processes and then assesses the parametrical interdependencies of two entities, namely the data analysis and data visualization techniques, which form the core of machine learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also includes case studies that employ machine learning for manufacturing processes in the engineering domain. The book not only provides beginners with an introduction to machine learning for applied sciences, enabling them to address global competitiveness and work on real-time technical challenges, it is also a valuable resource for scholars with domain knowledge. From the Back Cover This book presents machine learning as a set of pre-requisites, co-requisites, and post-requisites, focusing on mathematical concepts and engineering applications in advanced welding and cutting processes. It describes a number of advanced welding and cutting processes and then assesses the parametrical interdependencies of two entities, namely the data analysis and data visualization techniques, which form the core of machine learning. Subsequently, it discusses supervised learning, highlighting Python libraries such as NumPy, Pandas and Scikit Learn programming. It also includes case studies that employ machine learning for manufacturing processes in the engineering domain. The book not only provides beginners with an introduction to machine learning for applied sciences, enabling them to address global competitiveness and work on real-time technical challenges, it is also a valuable resource for scholars with domain knowledge. About the Author Dr. S. Arungalai Vendan is an Associate Professor, Innovation Labs, School of Engineering, Dayananda Sagar University, Bangalore, India. He has been working on advanced welding processes since 2006. He received his Ph.D. degree from the National Institute of Technology, Tiruchirappalli, India in 2010. He has successfully completed several government-funded research projects and industrial consultancy projects, and has published more than 100 research papers in international journals and conference proceedings. His research interests mainly focus on the interdisciplinary science which has confluence of terminologies from electrical/mechanical/metallurgical/materials and magnetic technologies.  Dr. Rajeev Kamal received his B.Tech. and M.Tech. degrees in Electronics & Communication Engineering and VLSI design from Dr. A.P.J. Abdul Kalam Technical University Uttar Pradesh and Guru Gobind Singh Indraprastha University, India in 2006 and 2008 respectively and the Ph.D. degree in Electronics Engineering from Technical University of Catalonia, Spain, in 2017. Since January 2018, he has been in the Department of Electronics Engineering, School of Engineering, Dayananda Sagar University as an Associate Professor. Dr. Rajeev focuses on the research of On-chip interconnection infrastructure and System on chip architecture. His recent research interests include: Globally Asynchronous locally Synchronous System, System on Chip, FPGA Architecture for the AI/ML. Dr. Rajeev has published several peer-reviewed technical papers in international journals and conferences. He is a member of IEEE and served as a reviewer of several international journals. He was a recipient of Postgrads fellowship award from Indian governments during his M.Tech. His received three Best Paper Awards at the IEEE International Conference held in India.  Mr. Abhinav Karan is an Assistant Professor in the Department of Electronics and Communication, School of Engineering, Dayananda Sagar University, Bangalore, India. He obtained his