eBook - ePub
Math Optimization for Artificial Intelligence
Heuristic and Metaheuristic Methods for Robotics and Machine Learning
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
Math Optimization for Artificial Intelligence
Heuristic and Metaheuristic Methods for Robotics and Machine Learning
About this book
The book presents powerful optimization approaches for integrating AI into daily life.
This book explores how heuristic and metaheuristic methodologies have revolutionized the fields of robotics and machine learning. The book covers the wide range of tools and methods that have emerged as part of the AI revolution, from state-of-the-art decision-making algorithms for robots to data-driven machine learning models. Each chapter offers a meticulous examination of the theoretical foundations and practical applications of mathematical optimization, helping readers understand how these methods are transforming the field of technology.
This book is an invaluable resource for researchers, practitioners, and students. It makes AI optimization accessible and comprehensible, equipping the next generation of innovators with the knowledge and skills to further advance robotics and machine learning. While artificial intelligence constantly evolves, this book sheds light on the path ahead.
This book explores how heuristic and metaheuristic methodologies have revolutionized the fields of robotics and machine learning. The book covers the wide range of tools and methods that have emerged as part of the AI revolution, from state-of-the-art decision-making algorithms for robots to data-driven machine learning models. Each chapter offers a meticulous examination of the theoretical foundations and practical applications of mathematical optimization, helping readers understand how these methods are transforming the field of technology.
This book is an invaluable resource for researchers, practitioners, and students. It makes AI optimization accessible and comprehensible, equipping the next generation of innovators with the knowledge and skills to further advance robotics and machine learning. While artificial intelligence constantly evolves, this book sheds light on the path ahead.
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Yes, you can access Math Optimization for Artificial Intelligence by Umesh Kumar Lilhore,Vishal Dutt,T. Ananth Kumar,Martin Margala,Kaamran Raahemifar in PDF and/or ePUB format, as well as other popular books in Mathematics & IT Industry. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Title Page
- Copyright
- Contents
- List of Authors
- 1âThe Role of Mathematical Optimization in Advanced AI Applications
- 2âAn Overview of Mathematical Optimization in Artificial Intelligence
- 3âRobust Optimization Methods for Ensuring AI System Reliability
- 4âSwarm Intelligence and Optimization in AI
- 5âPrivacy and Security for 6Gâs IoT-Connected Future in the Age of Quantum Computing
- 6âOptimization in Natural Language Processing Models for Enhanced Performance and Efficiency
- 7âUnveiling the Intriguing Applications of Mathematical Optimization in Artificial Intelligence
- 8âUnleashing the Power of Evolutionary Algorithms: Advanced Optimization Techniques in Artificial Intelligence
- 9âIntroduction to Mathematical Optimization Techniques in AI
- 10âHybrid Mathematical Optimization Techniques in AI
- 11âMathematical Optimization for Enhanced AI-Enabled Geospatial Intelligence
- 12âDeep Learning-Based Ultrasound Analysis Using Explainable Artificial Intelligence (XAI) Methods for Breast Cancer
- 13âExplainable Artificial Intelligence Techniques in Deep Learning-Based Liver Tumor Analysis
- 14âA Novel African Wild Dog Optimization (AWDO) Algorithm for Applications of Artificial Intelligence
- 15âArtificial Intelligence-Based Control Strategies for COVID-19 That Target Different Age Groups
- 16âModel Optimization in Deep Learning: Theory and Application
- 17âQuantitative Analysis for LMS Using Mathematical Modeling by Artificial Intelligence
- 18âOptimizing Neural Network Training by Addressing Key Challenges and Advanced Techniques
- 19âPrinciples and Applications of Bayesian Optimization in AI
- Index