Deep and Shallow: Machine Learning in Music and Audio, Dubnov, Shlomo ; Greer, Ross
Автор: Zhang Wengang, Zhang Yanmei, Gu Xin Название: Application of Soft Computing, Machine Learning, Deep Learning and Optimizations in Geoengineering and Geoscience ISBN: 9811668345 ISBN-13(EAN): 9789811668340 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book summarizes the application of soft computing techniques, machine learning approaches, deep learning algorithms and optimization techniques in geoengineering including tunnelling, excavation, pipelines, etc.
Автор: Abedin Название: Novel Financial Applications of Machine Learning and Deep Learning ISBN: 303118551X ISBN-13(EAN): 9783031185519 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study. The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice. The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Автор: Hu, Fei Название: AI, Machine Learning and Deep Learning ISBN: 1032034041 ISBN-13(EAN): 9781032034041 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Bartz Название: Hyperparameter Tuning for Machine and Deep Learning with R ISBN: 9811951691 ISBN-13(EAN): 9789811951695 Издательство: Springer Рейтинг: Цена: 37260.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. No high-performance computing facilities are required. The idea for the book originated in a study conducted by Bartz & Bartz GmbH for the Federal Statistical Office of Germany (Destatis). Building on that study, the book is addressed to practitioners in industry as well as researchers, teachers and students in academia. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II). Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms. The book presents analyses of more than 30 hyperparameters from six relevant ML and DL methods, and provides source code so that users can reproduce the results. Accordingly, it serves as a handbook and textbook alike.
Автор: Vatsa, Mayank ; Singh, Richa ; Majumdar, Angshul Название: Deep Learning in Biometrics ISBN: 1032653108 ISBN-13(EAN): 9781032653105 Издательство: Taylor&Francis Рейтинг: Цена: 51030.00 T Наличие на складе: Нет в наличии.
Автор: Abu Bakar Abdul Hamid, Madhu Sharma Gaur, Noor Inayah Binti Ya`akub, Rajeev Kumar, Sanjeev Kumar Название: Futuristic E-Governance Security with Deep Learning Applications ISBN: 1668495961 ISBN-13(EAN): 9781668495964 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 286440.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In today's rapidly advancing digital world, governments are increasingly relying on technology to enhance security systems and streamline governance. However, this growing reliance on digital platforms and data collection also presents significant challenges. Cybersecurity threats and privacy concerns pose large risks to sensitive information and can potentially leading to inaccuracies or breaches within deep learning models. There is a pressing need for comprehensive solutions that address these security issues and protect valuable data in the realm of e-governance. Futuristic e-Governance Security With Deep Learning Applications is a timely and indispensable resource that offers a holistic approach to tackling the security challenges of the digital era. The book presents a global perspective on the integration of intelligent systems with cybersecurity applications, highlighting cutting-edge techniques and methodologies to safeguard deep learning models from security attacks and privacy vulnerabilities. By exploring the latest advances and countermeasures in deep learning, this book equips scholars, researchers, and industry experts with the knowledge and tools they need to address security concerns and develop robust e-governance systems. This comprehensive volume not only sheds light on the current state-of-the-art methods but also delves into future trends and challenges. From skill development and tools for intelligence systems to deep learning, machine learning, blockchain, IoT, and cloud computing, the book covers a wide range of topics essential to understanding and implementing secure e-governance systems. With its practical insights and interdisciplinary approach, this book serves as a vital resource for academics, researchers, and professionals seeking to navigate the complex landscape of e-governance security and leverage deep learning applications to protect valuable data and ensure the smooth functioning of government operations.
Автор: Dubnov, Shlomo Greer, Ross Название: Deep and shallow ISBN: 1032133910 ISBN-13(EAN): 9781032133911 Издательство: Taylor&Francis Рейтинг: Цена: 45930.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Suganthi K., Karthik R., Rajesh G. Название: Machine Learning and Deep Learning Techniques in Wireless and Mobile Networking Systems ISBN: 0367620065 ISBN-13(EAN): 9780367620066 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers the latest advances and results in the fields of machine learning and deep learning for wireless communications and provides positive discussions on the challenges and prospects. It includes a broad spectrum in understanding the improvements motivated by specific constraints posed by wireless communications.
Автор: McFee, Brian Название: Digital Signals Theory ISBN: 1032207140 ISBN-13(EAN): 9781032207148 Издательство: Taylor&Francis Рейтинг: Цена: 122490.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Padmavathi Ganapathi, D. Shanmugapriya Название: Handbook of Research on Machine and Deep Learning Applications for Cyber Security ISBN: 1522596119 ISBN-13(EAN): 9781522596110 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 264270.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: As the advancement of technology continues, cyber security continues to play a significant role in today's world. With society becoming more dependent on the internet, new opportunities for virtual attacks can lead to the exposure of critical information. Machine and deep learning techniques to prevent this exposure of information are being applied to address mounting concerns in computer security.
The Handbook of Research on Machine and Deep Learning Applications for Cyber Security is a pivotal reference source that provides vital research on the application of machine learning techniques for network security research. While highlighting topics such as web security, malware detection, and secure information sharing, this publication explores recent research findings in the area of electronic security as well as challenges and countermeasures in cyber security research. It is ideally designed for software engineers, IT specialists, cybersecurity analysts, industrial experts, academicians, researchers, and post-graduate students.
Название: Smart agriculture ISBN: 0367687682 ISBN-13(EAN): 9780367687687 Издательство: Taylor&Francis Рейтинг: Цена: 46950.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures.
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