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Editorial: Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC)

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Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 915))

Abstract

Machine learning (ML) is the subcategory of artificial intelligence (AI), which has the capability to imitate human behavior intelligently as per the task performed by the human. In the modern time, any organization implements AI by using ML so that system’s behavior of interchangeably and ambiguously is updated automatically through the experience without any delay. So, current advances in AI have involved ML. The ML starts with data (i.e., any kind of data starting from primary to secondary data). These data are collected and preprocessed to be used as training and testing the ML models being utilized for different applications such as regression, prediction, forecasting, classification, clustering, management, design, optimization, security, IoTs, health care, digitization, automation, control, privacy protection and e-commerce. In this book, the applications AI, ML and its advancement for different applications have been presented into different chapters, including the state-of-the-art and implementation in the various research domains of engineering and science.

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Acknowledgements

The editors would like to acknowledge the support from Krishna Engineering College (KEC), Ghaziabad, India to manage the event of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC-2021) - Virtual Mode. The editors extend their appreciation and acknowledgement to the Intelligent Prognostic Private Limited, India, to provide all types of technical and non-technical facilities, cooperation and support in each stage to make this book real.

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Authors and Affiliations

  1. ICE Division, NSUT, New Delhi, India

    A. Tomar

  2. Division of Electrical Power Engineering, School of Electrical Engineering, Faculty of Engineering, University of Technology Malaysia (UTM), Johor Bahru, Malaysia

    H. Malik

  3. Department of Computer Science & Engineering, KEC, Mumbai, India

    P. Kumr

  4. Department of Electrical Engineering, Qatar University, Doha, Qatar

    A. Iqbal

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Editors and Affiliations

  1. Division of Instrumentation and Control Engineering, Netaji Subhas University of Technology, Delhi, India

    Anuradha Tomar

  2. Division of Electrical Power Engineering, Faculty of Engineering, School of Electrical Engineering, University of Technology Malaysia (UTM), Johor Bahru, Malaysia

    Hasmat Malik

  3. Department of Computer Science and Engineering, Krishna Engineering College, Uttar Pradesh, India

    Pramod Kumar

  4. Department of Electrical Engineering, Qatar University, Doha, Qatar

    Atif Iqbal

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Tomar, A., Malik, H., Kumr, P., Iqbal, A. (2022). Editorial: Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC). In: Tomar, A., Malik, H., Kumar, P., Iqbal, A. (eds) Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication. Lecture Notes in Electrical Engineering, vol 915. Springer, Singapore. https://doi.org/10.1007/978-981-19-2828-4_1

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