machine learning optimization techniques (127 resultados)

hardcover. Condición: Very Good. The Science of Algorithmic Trading and Portfolio Management: Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days. 453.

Paperback. Condición: Brand New. 109 pages. 11.69x8.27x0.28 inches. In Stock.

Condición: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher.

Condición: Wie Neu. Zustandsbeschreibung: leichte Lagerspuren, leicht bestoßen/minor shelfwear, slightly bumped. Edited by Vipin Kumar Kukkala and Sudeep Pasricha. With contributions by Wanli Chang, Nan Chen, Shuai Zhao, Xiaotian Dai et al. XV,789 Seiten, gebunden (Springer-Verlag 2023). Statt EUR 117,69. Gewicht: 137 g - Gebunden/Gebundene Ausgabe - Sprache: Englisch.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: New. 2024. Paperback. . . . . .

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Distributed machine learning and optimization techniques are transforming the field of artificial intelligence by enabling the creation of scalable and efficient algorithms for complex problems. This book provides a comprehensive overview of the latest advancements in distributed machine learning and optimization, highlighting their potential applications in fields such as natural language processing, computer vision, and predictive analytics. By examining the underlying principles and techniques, it reveals the vast possibilities for harnessing the power of distributed machine learning and optimization to create innovative solutions for real-world problems. The Distributed Machine Learning and Optimization Techniques book offers a cutting-edge exploration of the rapidly evolving field of distributed machine learning and optimization. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Railway Signaling and Data Mining and Machine Learning Techniques and Optimization presents a comprehensive exploration of the intricate relationships between railway signaling, data mining, and machine learning techniques. This book provides a nuanced understanding of the complex dynamics at play in modern railway systems, where data-driven insights and machine learning algorithms are increasingly being leveraged to optimize performance and safety. By examining the intersections of these fields, Railway Signaling and Data Mining and Machine Learning Techniques and Optimization offers a cutting-edge perspective on the future of railway engineering and operations. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. The supply chain is a complex web of interconnected systems, and optimizing its performance requires a deep understanding of the underlying dynamics. 'Machine Learning for Supply Chain Optimization Techniques' offers a cutting-edge approach to supply chain management, leveraging the power of machine learning to identify patterns and predict outcomes. By applying machine learning algorithms to real-world supply chain data, this book provides a detailed analysis of the key factors that influence supply chain performance. From demand forecasting and inventory management to logistics and transportation, this book offers a comprehensive framework for optimizing the supply chain. By harnessing the power of machine learning, this book enables readers to make data-driven decisions and drive business success. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Code Optimization Techniques for Machine Learning Models offers a cutting-edge exploration of the latest techniques and strategies for optimizing machine learning models. This book provides a comprehensive and in-depth examination of the principles and practices of code optimization, including the use of profiling tools, the optimization of neural networks, and the application of machine learning algorithms. With its practical examples, real-world case studies, and expert insights, Code Optimization Techniques for Machine Learning Models is an essential resource for machine learning engineers, data scientists, and anyone interested in improving the performance and efficiency of their machine learning models. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. The integration of machine learning in renewable energy systems is revolutionizing the way we generate, distribute, and consume energy. 'Machine Learning Techniques for Renewable Energy Optimization' provides a comprehensive guide to the application of machine learning techniques in renewable energy optimization. By exploring the theoretical foundations and practical implementations of machine learning in renewable energy, readers can develop effective strategies for maximizing energy efficiency, reducing costs, and mitigating the impact of climate change. This book offers a valuable resource for researchers, practitioners, and policymakers seeking to unlock the full potential of machine learning in renewable energy. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. 'Machine Learning Techniques for HVAC Optimization' presents innovative approaches to enhancing heating, ventilation, and air conditioning systems through advanced algorithms. The book demonstrates how machine learning models can predict environmental changes, optimize energy consumption, and improve overall system efficiency. It covers various techniques such as neural networks, reinforcement learning, and data analytics, illustrating their application in real-world scenarios. This resource is essential for understanding how intelligent algorithms can revolutionize climate control in residential and commercial spaces, leading to sustainable and cost-effective solutions. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Condición: New. In.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. The Math of Optimization Techniques for Machine Learning presents a comprehensive overview of the mathematical frameworks that underlie the optimization processes driving machine learning systems. This in-depth exploration of the intricate relationships between mathematical models, computational algorithms, and machine learning outcomes offers a profound understanding of the complex dynamics governing the performance of machine learning models. By examining the mathematical underpinnings of optimization techniques, this book provides a rigorous foundation for the development of more efficient and effective machine learning systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Hardcover. Condición: New.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Railway Signaling and Graph Theoretic Analysis and Optimization Techniques and Machine Learning presents a novel application of graph theory to the complex domain of railway signaling. This book explores the strategic interactions between trains, signals, and track infrastructure, revealing new opportunities for optimizing performance and safety. By leveraging machine learning algorithms and graph models, Railway Signaling and Graph Theoretic Analysis and Optimization Techniques and Machine Learning offers a forward-thinking approach to railway operations and management. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Condición: New. SUPER FAST SHIPPING.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Inventory optimization is a critical component of supply chain management, and machine learning has emerged as a powerful tool for optimizing inventory levels. "Inventory Optimization with Machine Learning Techniques for Supply Chain" explores the latest advancements in machine learning for inventory optimization, including predictive analytics, clustering, and decision trees. This book provides a comprehensive overview of machine learning techniques for inventory optimization, including their design, implementation, and deployment. With its focus on supply chain, this book is an essential resource for supply chain professionals, logistics experts, and business leaders looking to harness the power of machine learning for inventory optimization. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. In the world of software development, code optimization is a critical aspect of delivering high-performance applications. This book provides a comprehensive guide to code optimization using machine learning techniques, offering practical advice on how to improve code efficiency and reduce computational complexity. By exploring the latest machine learning algorithms and techniques, readers can develop a deeper understanding of the optimization strategies required to deliver fast, scalable, and reliable software. The book examines the key challenges of code optimization, including data preprocessing, feature engineering, and model selection. It also provides a framework for developing and deploying optimized code, including techniques for hyperparameter tuning and model ensembling. By mastering the art of code optimization, readers can deliver high-quality software that meets the demands of modern applications. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Portfolio Optimization Techniques Using AI & Machine Learning presents advanced methodologies for refining investment allocations through cutting-edge technology. This book showcases how artificial intelligence and machine learning algorithms can identify optimal asset mixes, predict market trends, and reduce risks in real estate portfolios. It emphasizes the transformative power of data-driven decision-making, offering practical insights into implementing these tools effectively. The focus is on enhancing portfolio performance by leveraging technological innovations, enabling investors to navigate complex markets with greater precision and confidence. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Condición: New. In.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of machine learning and imaging. The present book is a collection of recent contributions in the field of optimization, either revisiting consolidated ideas to provide formal theoretical guarantees or providing comparative numerical studies for challenging inverse problems in imaging. The work of these papers originated in the INdAM Workshop 'Advanced Techniques in Optimization for Machine learning and Imaging' held in Roma, Italy, on June 20-24, 2022.The covered topics include non-smooth optimisation techniques for model-driven variational regularization, fixed-point continuation algorithms and their theoretical analysis for selection strategies of the regularization parameter for linear inverse problems in imaging, different perspectives on Support Vector Machines trained via Majorization-Minimization methods, generalization of Bayesian statistical frameworks to imaging problems, and creation of benchmark datasets for testing new methods and algorithms.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Railway Signaling and Combinatorial Optimization and Machine Learning Techniques and Optimization presents a comprehensive exploration of the intricate relationships between railway signaling, combinatorial optimization, and machine learning techniques. This book provides a nuanced understanding of the complex dynamics at play in modern railway systems, where data-driven insights and machine learning algorithms are increasingly being leveraged to optimize performance and safety. By examining the intersections of these fields, Railway Signaling and Combinatorial Optimization and Machine Learning Techniques and Optimization offers a cutting-edge perspective on the future of railway engineering and operations. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Cache memory optimization is a critical aspect of machine learning model performance. Cache Memory Optimization Techniques for Machine Learning provides a thorough examination of the techniques and strategies required to optimize cache memory usage, resulting in faster model execution and improved accuracy. By leveraging the power of cache memory, developers can significantly enhance their model's performance, reduce training times, and increase overall efficiency. This book covers the fundamental concepts of cache memory, its impact on machine learning models, and the various optimization techniques available, making it a valuable resource for machine learning practitioners. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. In 'Machine Learning Techniques for HVAC Optimization', discover the innovative applications of machine learning in optimizing heating, ventilation, and air conditioning (HVAC) systems. By exploring the various machine learning algorithms and techniques used in HVAC optimization, this book provides a comprehensive understanding of the role machine learning plays in streamlining HVAC processes. From designing machine learning-driven HVAC systems to integrating smart home sensors, every aspect of machine learning in HVAC optimization is thoroughly examined. By the end of this exploration, you'll gain a deeper appreciation for the vast potential of machine learning in transforming the way we control and optimize HVAC systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Inventory Optimization with Machine Learning Techniques offers a data-driven approach to optimizing inventory levels and reducing waste. By applying machine learning algorithms to inventory data, organizations can identify patterns and trends that inform inventory decisions. This book provides a comprehensive overview of machine learning techniques, including predictive analytics, clustering, and decision trees. With Inventory Optimization with Machine Learning Techniques, readers will learn how to use machine learning to optimize inventory levels, reduce costs, and improve supply chain efficiency. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Machine Learning for Industrial Efficiency Optimization Techniques presents a cutting-edge approach to industrial efficiency optimization, leveraging the power of machine learning to drive business results. By applying machine learning algorithms to industrial data and other relevant information, this book shows how to identify opportunities for improvement, optimize processes, and reduce waste. With a focus on real-world examples and case studies, Machine Learning for Industrial Efficiency Optimization Techniques provides a practical guide for industrial professionals seeking to implement machine learning-based optimization strategies. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Railway Signaling and Game Theoretic Analysis and Optimization Techniques and Machine Learning presents a novel application of game theory to the complex domain of railway signaling. This book explores the strategic interactions between trains, signals, and track infrastructure, revealing new opportunities for optimizing performance and safety. By leveraging machine learning algorithms and game-theoretic models, Railway Signaling and Game Theoretic Analysis and Optimization Techniques and Machine Learning offers a forward-thinking approach to railway operations and management. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.