Machine learning for smart healthcare / Rehab A. Rayan -- Predictive analysis for flood risk mapping utilizing machine learning approach / Aditya Singh, Sunil Khatri, Sandhya Save, Hemant Kasturiwale -- Dependability analysis on CPs using machine learning techniques / S. Krishna Narayanan, S. Dhanasekaran, V. Vasudevan -- Machine learning for risk analysis / Parita Jain, Puneet Kumar Aggarwal, Kshirja Makar, Riya Garg, Jaya Mehta, Poorvi Chaudhary -- Machine learning techniques enabled electric vehicle / M. Shyamalagowri, G Revathy -- A comparative analysis of established techniques and their applications in the field of gesture detection / Muskan Jindal, Eshan Bajal, Shilpi Sharma -- Brain-computer-interface for dream visualization using deep learning / Brijesh K. Soni, Akhilesh A. Waoo -- Machine learning and data analysis based breast cancer classification / Souvik Das, K Rama Chaitanya, O B Krishna, and J Maiti -- Accurate automatic functional recognition of proteins : overview and current computational challenges / Javier Pérez-Rodríguez, Morteza Yazdani, Prasenjit Chatterjee -- Taxonomy of shilling attack detection techniques in recommender system / Abhishek Majumder, Keya Chowdhury, Joy Lal Sarkar -- Machine learning applications in real-world time series problems / Antonio Manuel Durán-Rosal, David Guijo-Rubio, Morteza Yazdani, Prasenjit Chatterjee -- Prediction of selective laser sintering part quality using deep learning / Lokesh Kumar Saxena, Pramod Kumar Jain -- CBPP : an efficient algorithm for privacy preserving data publishing of 1 : M micro data with multiple sensitive attributes / Jayapradha. J, Prakash. M -- Classification of network traffic on ISP link and analysis of network bandwidth during COVID-19 / Ajantha Devi. V, Yogendra Malgundkar, Bandana Mahapatra -- Integration of AI/Ml in 5G technology toward intelligent connectivity, security, and challenges / Devasis Pradhan, Prasanna Kumar Sahu, Rajeswari, Hla Myo Tun, Naw Khu Say Wah.

"Machine Learning (ML) is a sub field of artificial intelligence that uses soft computing and algorithms to enable computers to learn on their own and identify patterns in observed data, build models that explain the world, and predict things without having explicit pre-programmed rules and models. This book discusses various applications of ML in engineering fields and the use of ML algorithms in solving challenging engineering problems ranging from biomedical, transport, supply chain and logistics, to manufacturing and industrial. Through numerous case studies, it will assist researchers and practitioners in selecting the correct options and strategies for managing organizational tasks"-- Provided by publisher.

OCLC-licensed vendor bibliographic record.