Data Mining and Machine Learning in High-Performance Sport, Muazu Musa
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10061.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Rino Micheloni, Cristian Zambelli Название: Machine Learning and Non-volatile Memories ISBN: 3031038401 ISBN-13(EAN): 9783031038402 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents the basics of both NAND flash storage and machine learning, detailing the storage problems the latter can help to solve. At a first sight, machine learning and non-volatile memories seem very far away from each other. Machine learning implies mathematics, algorithms and a lot of computation; non-volatile memories are solid-state devices used to store information, having the amazing capability of retaining the information even without power supply.
This book will help the reader understand how these two worlds can work together, bringing a lot of value to each other. In particular, the book covers two main fields of application: analog neural networks (NNs) and solid-state drives (SSDs). After reviewing the basics of machine learning in Chapter 1, Chapter 2 shows how neural networks can mimic the human brain; to accomplish this result, neural networks have to perform a specific computation called vector-by-matrix (VbM) multiplication, which is particularly power hungry.
In the digital domain, VbM is implemented by means of logic gates which dictate both the area occupation and the power consumption; the combination of the two poses serious challenges to the hardware scalability, thus limiting the size of the neural network itself, especially in terms of the number of processable inputs and outputs. Non-volatile memories (phase change memories in Chapter 3, resistive memories in Chapter 4, and 3D flash memories in Chapter 5 and Chapter 6) enable the analog implementation of the VbM (also called "neuromorphic architecture"), which can easily beat the equivalent digital implementation in terms of both speed and energy consumption. SSDs and flash memories are strictly coupled together; as 3D flash scales, there is a significant amount of work that has to be done in order to optimize the overall performances of SSDs.
Machine learning has emerged as a viable solution in many stages of this process. After introducing the main flash reliability issues, Chapter 7 shows both supervised and un-supervised machine learning techniques that can be applied to NAND. In addition, Chapter 7 deals with algorithms and techniques for a pro-active reliability management of SSDs.
Last but not least, the last section of Chapter 7 discusses the next challenge for machine learning in the context of the so-called computational storage. No doubt that machine learning and non-volatile memories can help each other, but we are just at the beginning of the journey; this book helps researchers understand the basics of each field by providing real application examples, hopefully, providing a good starting point for the next level of development.
Название: High Performance Programming for Soft Computing ISBN: 146658601X ISBN-13(EAN): 9781466586017 Издательство: Taylor&Francis Рейтинг: Цена: 22968.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book examines the present and future of soft computer techniques. It explains how to use the latest technological tools, such as multicore processors and graphics processing units, to implement highly efficient intelligent system methods using a general purpose computer.
Автор: Brij B. Gupta, Quan Z. Sheng Название: Machine Learning for Computer and Cyber Security ISBN: 1138587303 ISBN-13(EAN): 9781138587304 Издательство: Taylor&Francis Рейтинг: Цена: 28327.00 р. Наличие на складе: Нет в наличии.
Описание: This comprehensive book offers valuable insights while using a wealth of examples and illustrations to effectively demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security.
Автор: Charu C. Aggarwal Название: Machine Learning for Text ISBN: 3030088073 ISBN-13(EAN): 9783030088071 Издательство: Springer Рейтинг: Цена: 6097.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Text analytics is a field that lies on the interface of information retrieval,machine learning, and natural language processing, and this textbook carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this textbook is organized into three categories:- Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for machine learning from text such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis.- Domain-sensitive mining: Chapters 8 and 9 discuss the learning methods from text when combined with different domains such as multimedia and the Web. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. - Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection. This textbook covers machine learning topics for text in detail. Since the coverage is extensive,multiple courses can be offered from the same book, depending on course level. Even though the presentation is text-centric, Chapters 3 to 7 cover machine learning algorithms that are often used indomains beyond text data. Therefore, the book can be used to offer courses not just in text analytics but also from the broader perspective of machine learning (with text as a backdrop). This textbook targets graduate students in computer science, as well as researchers, professors, and industrial practitioners working in these related fields. This textbook is accompanied with a solution manual for classroom teaching.
Автор: Pablo Duboue Название: The Art of Feature Engineering: Essentials for Machine Learning ISBN: 1108709389 ISBN-13(EAN): 9781108709385 Издательство: Cambridge Academ Рейтинг: Цена: 6970.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is a guide for data scientists who want to use feature engineering to improve the performance of their machine learning solutions. The book provides a unified view of the field, beginning with basic concepts and techniques, followed by a cross-domain approach to advanced topics, like texts and images, with hands-on case studies.
Автор: Pedro Larran?aga; Alberto Ogbechie Название: Industrial Applications of Machine Learning ISBN: 0367656876 ISBN-13(EAN): 9780367656874 Издательство: Taylor&Francis Рейтинг: Цена: 7654.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book shows how machine learning can be applied to address real-world problems in the fourth industrial revolution and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society
Автор: Lucio Grandinetti; Seyedeh Leili Mirtaheri; Reza S Название: High-Performance Computing and Big Data Analysis ISBN: 3030334945 ISBN-13(EAN): 9783030334949 Издательство: Springer Рейтинг: Цена: 11220.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes revised and selected papers from the Second International Congress on High-Performance Computing and Big Data Analysis, TopHPC 2019, held in Tehran, Iran, in April 2019.
The 37 full papers and 2 short papers presented in this volume were carefully reviewed and selected from a total of 103 submissions. The papers in the volume are organized acording to the following topical headings: deep learning; big data analytics; Internet of Things.- data mining, neural network and genetic algorithms; performance issuesand quantum computing.
Описание: This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications.
Автор: Baddi Youssef, Gahi Youssef, Maleh Yassine Название: Big Data Intelligence for Smart Applications ISBN: 3030879534 ISBN-13(EAN): 9783030879532 Издательство: Springer Рейтинг: Цена: 21953.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Today, the use of machine intelligence, expert systems, and analytical technologies combined with Big Data is the natural evolution of both disciplines. As a result, there is a pressing need for new and innovative algorithms to help us find effective and practical solutions for smart applications such as smart cities, IoT, healthcare, and cybersecurity. This book presents the latest advances in big data intelligence for smart applications. It explores several problems and their solutions regarding computational intelligence and big data for smart applications. It also discusses new models, practical solutions,and technological advances related to developing and transforming cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.
Автор: Vбzquez-Herrero Jorge, Silva-Rodrнguez Alba, Negreira-Rey Marнa-Cruz Название: Total Journalism: Models, Techniques and Challenges ISBN: 3030880273 ISBN-13(EAN): 9783030880279 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book aims to explore the diverse landscape of journalism in the third decade of the twenty-first century, constantly changing and still dealing with the consequences of a global pandemic. ‘Total journalism’ is the concept that refers to the renewed and current journalism that employs all available techniques, technologies, and platforms. Authors discuss the innovative nature of journalism, the influence of big data and information disorders, models, professionals and audiences, as well as the challenges of artificial intelligence. The book gives an up-to-date overview of these perspectives on journalistic production and distribution. The effects of misinformation and the challenge of artificial intelligence are of specific relevance in this book. Readers can enjoy with contributions from prestigious experts and researchers who make this book an interesting resource for media professionals and researchers in media and communication studies.
Описание: This brief highlights the application of performance analysis tools in data acquisition, and various machine learning algorithms for evaluating team performance as well as talent identification in beach soccer and sepak takraw.
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