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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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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 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 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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Prashad
Optimization Algorithms for Machine Learning: Theory and Practice

In the realm of machine learning, optimization algorithms play a pivotal role in refining models for optimal performance. These algorithms, ranging from classic gradient descent to advanced techniques lik…

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Tsutomu Sasao
Classification Functions for Machine Learning and Data Mining

This book introduces a novel perspective on machine learning, offering distinct advantages over neural network-based techniques. This approach boasts a reduced hardware requirement, lower power consumptio…

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Machine Learning Methods for Multi-Omics Data Integration

The advancement of biomedical engineering has enabled the generation of multi-omics data by developing high-throughput technologies, such as next-generation sequencing, mass spectrometry, and microarrays.…

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Practical Machine Learning Tools and Techniques for Industrial Applications

The main goal of the book is to provide a comprehensive and accessible guide that empowers readers to understand, apply, and leverage machine learning algorithms and techniques effectively in real-world s…

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Anupam Bagchi, Pramod Gupta
Essentials of Python for Artificial Intelligence and Machine Learning

This book introduces the essentials of Python for the emerging fields of Machine Learning (ML) and Artificial Intelligence (AI). The authors explore the use of Python's advanced module features and apply …

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Harnessing AI, Machine Learning, and IoT for Intelligent Business

This book addresses the growing need for understanding the practical implications of these technologies in the context of financial management. The convergence of AI, ML, and IoT has revolutionized variou…

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Harnessing AI, Machine Learning, and IoT for Intelligent Business

This book is a comprehensive guide that explores the integration of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) in the realm of business management and finance. T…

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Machine Learning Models and Architectures for Biomedical Signal Processing

Machine Learning Models and Architectures for Biomedical Signal Processing presents the fundamental concepts of machine learning techniques for bioinformatics in an interactive way. The book investigates …

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Jeffrey A. Fessler, Raj Rao Nadakuditi
Linear Algebra for Data Science, Machine Learning, and Signal Processing

"Master basic matrix methods by seeing how the math is used in practice in a range of data-driven applications. Includes a wealth of engaging exercises for quizzes, self-study and interactive learnin…

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Samuel Ackerman, Guy Barash, Onn Shehory, Orna Raz
Theory and Practice of Quality Assurance for Machine Learning Systems

This book is a self-contained introduction to engineering and testing machine learning (ML) systems. It systematically discusses and teaches the art of crafting and developing software systems that includ…

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Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems

This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent a…

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Uncertainty for Safe Utilization of Machine Learning in Medical Imaging

Lecture Notes in Computer Science - Band 15167

This book constitutes the refereed proceedings of the 6th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh,…

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Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing

Signal Processing Driven Machine Learning Techniques for Cardiovascular Data Processing features recent advances in machine learning coupled with new signal processing-based methods for cardiovascular dat…

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Maurizio Perticarini
Machine Learning and Mixed Reality for the Enhancement of Cultural Heritage

This book addresses the role of modern surveying and representation technologies in preserving and disseminating cultural heritage. A workflow is illustrated, describing the Former Monastery of Ss Severin…

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Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications

This volume presents a selection of articles on statistical modeling and simulation, with a focus on different aspects of statistical estimation and testing problems, the design of experiments, reliabilit…

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