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The book provides mathematicians an overview of AI and machine learning relevant to operations research. It focuses decision modeling and optimization models as well as algorithms.
The book provides mathematicians an overview of AI and machine learning relevant to operations research. It focuses decision modeling and optimization models as well as algorithms.
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Dr. Biswadip Basu Mallik is an associate professor of Mathematics in the Department of Basic Science & Humanities at Institute of Engineering & Management, University of Engineering & Management, Kolkata, India. Dr. Gunjan Mukherjee is an associate professor in the Department of Computational Science, Brainware University, Barasat, India. Rahul Kar holds a master's degree in mathematics from Burdwan University and is currently working as a SACT-II Mathematics faculty of Kalyani Mahavidyalaya, Kalyani, Nadia, West Bengal. Aryan Chaudhary is the chief scientific advisor at BioTech Sphere Research, India, and a recognized researcher of healthcare and technology.
Inhaltsangabe
1. Deep Learning: Overview, Applications and Computing Devices 2. Deep Learning Impacts in the Field of Artificial Intelligence 3. Deep Learning is a State-of-the-Art Approach to Artificial Intelligence 4. Unleashing the Power: Exploring Deep Learning Architecture for Cutting-Edge AI Solutions 5. Deep Learning for ECG Classification: Techniques, Applications, and Challenges 6. Social Distancing Detection System Using Single Shot Detection (SSD) and Neural Networks 7. Recognition of Voice and Speech Using NLP Techniques 8. Transfer Learning with Joint Fine-Tuning for Multimodal Sentiment Analysis 9. Machine Learning for Traffic Flow Prediction Addressing Congestion Challenges 10. Enhancing Autistic Spectrum Disorder Diagnosis Using ML Techniques: A Study on Deep Neural Network and Drop-out Deep Neural Network 11. Deep Learning: A State-of-the-Art Approach to Artificial Intelligence 12. An Approach through Different Mathematical Models to Enhance the Utility in Different Areas of Machine Learning 13. Study of Different Regression Methods, Models and Application in Deep Learning Paradigm 14. Deep Learning Impacts in the Field of Artificial Intelligence 15. Stock Prices Prediction of the FMCG Sector in NSE India: An Artificial Intelligence Approach 16. Multi-Attribute Decision Modelling 17. Regression Methods and Models 18. The Machine Learning Pipeline: Algorithms, Applications, and Managerial Implications 19. Role of Fertamean Neutrosophic Sets for Decision Making Modelling in Machine Learning 20. Performance Evaluation of Machine Learning Algorithms in the Field of Security-Malware Detection
1. Deep Learning: Overview, Applications and Computing Devices 2. Deep Learning Impacts in the Field of Artificial Intelligence 3. Deep Learning is a State-of-the-Art Approach to Artificial Intelligence 4. Unleashing the Power: Exploring Deep Learning Architecture for Cutting-Edge AI Solutions 5. Deep Learning for ECG Classification: Techniques, Applications, and Challenges 6. Social Distancing Detection System Using Single Shot Detection (SSD) and Neural Networks 7. Recognition of Voice and Speech Using NLP Techniques 8. Transfer Learning with Joint Fine-Tuning for Multimodal Sentiment Analysis 9. Machine Learning for Traffic Flow Prediction Addressing Congestion Challenges 10. Enhancing Autistic Spectrum Disorder Diagnosis Using ML Techniques: A Study on Deep Neural Network and Drop-out Deep Neural Network 11. Deep Learning: A State-of-the-Art Approach to Artificial Intelligence 12. An Approach through Different Mathematical Models to Enhance the Utility in Different Areas of Machine Learning 13. Study of Different Regression Methods, Models and Application in Deep Learning Paradigm 14. Deep Learning Impacts in the Field of Artificial Intelligence 15. Stock Prices Prediction of the FMCG Sector in NSE India: An Artificial Intelligence Approach 16. Multi-Attribute Decision Modelling 17. Regression Methods and Models 18. The Machine Learning Pipeline: Algorithms, Applications, and Managerial Implications 19. Role of Fertamean Neutrosophic Sets for Decision Making Modelling in Machine Learning 20. Performance Evaluation of Machine Learning Algorithms in the Field of Security-Malware Detection
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