Machine Learning For Optimization – alle Bücher, Seite 2

Modeling and Optimization of Signals Using Machine Learning Techniques

Explore the power of machine learning to revolutionize signal processing and optimization with cutting-edge techniques and practical insights in this outstanding new volume from Scrivener Publishing.Model…

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Machine Learning, Deep Learning and AI for Cybersecurity

This book addresses a variety of problems that arise at the interface between AI techniques and challenging problems in cybersecurity. The book covers many of the issues that arise when applying AI and de…

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Dieter Gerber
Optimization techniques for electrical machines

electromechanical devices in power generation and drive systems. It highlights the importance of improving the performance and energy efficiency of electrical machines, which consume a significant portion…

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Charu C. Aggarwal
Probability and Statistics for Machine Learning

This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories:*The basics of probability and statistics:*These chapters focus on t…

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Kinky
Exploring Optimization Algorithms in Machine Learning: From Theory to Practice

Optimization algorithms in machine learning bridge theoretical foundations with practical applications, crucial for refining model performance. Techniques like gradient descent, stochastic gradient descen…

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Eklas Hossain
Machine Learning Crash Course for Engineers

¿Machine Learning Crash Course for Engineersis a reader-friendly introductory guide to machine learning algorithms and techniques for students, engineers, and other busy technical professionals. The book …

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Machine Learning for Cyber-Physical Systems

This open access proceedings presents new approaches to Machine Learning for Cyber-Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS ¿ Ma…

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Machine Learning for Data Science Handbook

This book is a major update to the very successful first and second editions (2005 and 2010) of Data Mining and Knowledge Discovery Handbook. Since the last edition, this field has continued to evolve and…

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Yong Zhou, Yinan Zou, Youlong Wu, Yuanming Shi
Machine Learning for Low-Latency Communications

Machine Learning for Low-Latency Communications presents the principles and practice of various deep learning methodologies for mitigating three critical latency components: access latency, transmission l…

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Machine Learning Applications for Intelligent Energy Management

As carbon dioxide (CO2) emissions and other greenhouse gases constantly rise and constitute the main contributor to climate change, temperature rise and global warming, artificial intelligence, big data, …

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Machine Learning for Drone-Enabled IoT Networks

This book aims to explore the latest developments, challenges, and opportunities in the application of machine learning techniques to enhance the performance and efficiency of IoT networks assisted by aer…

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Vidya Subramanian
Applied Machine Learning for Data Science Practitioners

Applied Machine Learning for Data Science Practitioners Vidya SubramanianA single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (M…

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Qiang Huang
Domain-informed Machine Learning for Smart Manufacturing

This book introduces the state-of-the-art understanding on domain-informed machine learning (DIML) for advanced manufacturing. Methods and case studies presented in this volume show how complicated engine…

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Denisse L. Argote, Pedro A. López-García, Manuel A. Torres-García
Machine Learning for Archaeological Applications in R

This Element highlights the employment within archaeology of classification methods developed in the field of chemometrics, artificial intelligence, and Bayesian statistics. It also provides a detailed ex…

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Statistical Machine Learning for Engineering with Applications

This book offers a leisurely introduction to the concepts and methods of machine learning. Readers will learn about classification trees, Bayesian learning, neural networks and deep learning, the design o…

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Denisse L. Argote, Pedro A. López-García, Manuel A. Torres-García
Machine Learning for Archaeological Applications in R

This Element highlights the employment within archaeology of classification methods developed in the field of chemometrics, artificial intelligence, and Bayesian statistics. It also provides a detailed ex…

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Machine Learning for Indoor Localization and Navigation

While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other…

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Machine Learning for Econometrics and Related Topics

In the last decades, machine learning techniques ¿ especially techniques of deep learning ¿ led to numerous successes in many application areas, including economics. The use of machine learning in economi…

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Machine Learning and Data Mining for Sports Analytics

This book constitutes the refereed proceedings of the 11th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2024, held in Vilnius, Lithuania, on September 9, 2024.The …

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Computational Intelligence for Machine Learning and Healthcare Informatics

This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a uniqu…

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