Machine Learning Methods – alle Bücher, Seite 2

Automation 2024: Advances in Automation, Robotics and Measurement Techniques

This book presents the result of the most recent discussion among interdisciplinary specialists facing scientific and industrial challenges. The papers presented during the Automation 2024 Conference deal…

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Giovanni Cerulli
Fundamentals of Supervised Machine Learning

This book presents the fundamental theoretical notions of supervised machine learning along with a wide range of applications using Python, R, and Stata. It provides a balance between theory and applicati…

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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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Andreas Tilevik
Multivariate Statistics and Machine Learning in R For Beginners

This book is more than just a book -- it is a full course designed as an interactive guide for beginners in multivariate analysis. Combining theoretical videos with practical examples in R, it offers read…

lieferbar ab 8.11.2025.

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Jesse van Griensven The, Jose Rosas-Bustos, Roydon Andrew Fraser
Quantum Computing and Quantum Machine Learning for Engineers and Developers

This book guides readers from the foundations of quantum mechanics through advanced quantum algorithms (such as Shor's and Grover's) and state-of-the-art machine learning methods. By illustrating how thes…

lieferbar ab 2.11.2025.

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Emerging Challenges in Intelligent Management Information Systems

This book contains the second volume of proceedings of the ECAI 2024 Workshop on Intelligent Management Information Systems (IMIS 2024). IMIS 2024 was part of the 27th European Conference on Artificial In…

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Shallow Learning vs. Deep Learning

This book explores the ongoing debate between shallow and deep learning in the field of machine learning. It provides a comprehensive survey of machine learning methods, from shallow learning to deep lear…

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Quantum Machine Learning

Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode …

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Machine Learning in Water Treatment

Machine Learning in Water Treatment is a must-have for anyone interested in how artificial intelligence is transforming water treatment, offering practical insights, case studies, and a deep dive into cut…

lieferbar ab 21.10.2025.

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AI for Brain Lesion Detection and Trauma Video Action Recognition

This book constitutes the proceedings of the First BONBID-HIE Lesion Segmentation Challenge and the First Trauma Thompson Challenge, held in conjunction with MICCAI 2023, in Vancouver, BC, Canada, during …

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Malware

This book provides a holistic overview of current state of the art and practice in malware research as well as the challenges of malware research from multiple angles. It also provides step-by-step guides…

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Applying Machine Learning in Science Education Research

This open access textbook offers science education researchers a hands-on guide for learning, critically examining, and integrating machine learning (ML) methods into their science education research proj…

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Sören Jalas
Machine Learning Based Optimization of Laser-Plasma Accelerators

This book explores the application of machine learning-based methods, particularly Bayesian optimization, within the realm of laser-plasma accelerators. The book involves the implementation of Bayesian op…

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Theodoros Karakasidis, Avraam Charakopoulos
Time Series and Networks Analysis

Introduction.- Time series statistics.- Time domain analysis.- Correlation and causality.- Clustering time series.- Nonlinear analysis.- Complex network time series.- Topological properties of networks.- …

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Forecasting with Artificial Intelligence

This book is a comprehensive guide that explores the intersection of artificial intelligence and forecasting, providing the latest insights and trends in this rapidly evolving field.The book contains four…

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Erik Cuevas, Jorge Galvez, Omar Avalos, Fernando Wario
Machine Learning and Metaheuristic Computation

Learn to bridge the gap between machine learning and metaheuristic methods to solve problems in optimization approachesFew areas of technology have greater potential to revolutionize the globe than artifi…

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N. M. Anoop Krishnan, Ravinder Bhattoo, Hariprasad Kodamana
Machine Learning for Materials Discovery

Focusing on the fundamentals of machine learning, this book covers broad areas of data-driven modeling, ranging from simple regression to advanced machine learning and optimization methods for application…

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Computational Design of Battery Materials

This book presents an essential survey of the state of the art in the application of diverse computational methods to the interpretation, prediction, and design of high-performance battery materials. Rech…

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