Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Название: Mathematics for Machine Learning ISBN: 110845514X ISBN-13(EAN): 9781108455145 Издательство: Cambridge Academ Рейтинг: Цена: 42230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Автор: Goodfellow Ian, Bengio Yoshua, Courville Aaron Название: Deep Learning ISBN: 0262035618 ISBN-13(EAN): 9780262035613 Издательство: MIT Press Рейтинг: Цена: 90290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.
The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.
Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Автор: Knud Erik Skouby, Prashant Dhotre, Idong Название: 5G, cybersecurity and privacy in developing countries / ISBN: 8770226474 ISBN-13(EAN): 9788770226479 Издательство: Taylor&Francis Рейтинг: Цена: 107190.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Aesthetic colour photography under water, that is the theme of this unique picture book by Canadian artist Barbara Cole. In her very own style, the artist plays with light and reflections, creating images that seem weightless and almost painted. Text in English and German.
Автор: Bharat S. Rawal , Gunasekaran Manogaran , Alexender Peter Название: Cybersecurity and Identity Access Management ISBN: 9811926573 ISBN-13(EAN): 9789811926570 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook provides a comprehensive, thorough and up-to-date treatment of topics in cyber security, cyber-attacks, ethical hacking, and cyber crimes prevention.
Автор: Sandhu Kamaljeet Название: Handbook of Research on Advancing Cybersecurity for Digital Transformation ISBN: 179986975X ISBN-13(EAN): 9781799869757 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 318910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Cybersecurity has been gaining serious attention and recently has become an important topic of concern for organizations, government institutions, and largely for people interacting with digital online systems. As many individual and organizational activities continue to grow and are conducted in the digital environment, new vulnerabilities have arisen which have led to cybersecurity threats. The nature, source, reasons, and sophistication for cyberattacks are not clearly known or understood, and many times invisible cyber attackers are never traced or can never be found. Cyberattacks can only be known once the attack and the destruction have already taken place long after the attackers have left. Cybersecurity for computer systems has increasingly become important because the government, military, corporate, financial, critical infrastructure, and medical organizations rely heavily on digital network systems, which process and store large volumes of data on computer devices that are exchanged on the internet, and they are vulnerable to ""continuous"" cyberattacks. As cybersecurity has become a global concern, it needs to be clearly understood, and innovative solutions are required.
Advancing Cybersecurity for Digital Transformation: Opportunities and Challenges looks deeper into issues, problems, and innovative solutions and strategies that are linked to cybersecurity. This book will provide important knowledge that can impact the improvement of cybersecurity, which can add value in terms of innovation to solving cybersecurity threats. The chapters cover cybersecurity challenges, technologies, and solutions in the context of different industries and different types of threats. This book is ideal for cybersecurity researchers, professionals, scientists, scholars, and managers, as well as practitioners, stakeholders, researchers, academicians, and students interested in the latest advancements in cybersecurity for digital transformation.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data.
The updated edition of this practical book uses concrete examples, minimal theory, and three production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started.
Автор: Li, Chong Название: Reinforcement Learning for Cyber-Physical Systems with Cybersecurity Case Studies ISBN: 1138543535 ISBN-13(EAN): 9781138543539 Издательство: Taylor&Francis Рейтинг: Цена: 84710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces reinforcement learning, and provides novel ideas and use cases to demonstrate the benefits of using reinforcement learning for Cyber Physical Systems. Two important case studies on applying reinforcement learning to cybersecurity problems are included.
Автор: Maleh Yassine, Shojafar Mohammad, Alazab Mamoun Название: Machine Intelligence and Big Data Analytics for Cybersecurity Applications ISBN: 3030570231 ISBN-13(EAN): 9783030570231 Издательство: Springer Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis.
Автор: Maleh Yassine, Shojafar Mohammad, Alazab Mamoun Название: Machine Intelligence and Big Data Analytics for Cybersecurity Applications ISBN: 3030570266 ISBN-13(EAN): 9783030570262 Издательство: Springer Рейтинг: Цена: 186330.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis.
Автор: Tsukerman Emmanuel Название: Machine Learning for Cybersecurity Cookbook ISBN: 1789614678 ISBN-13(EAN): 9781789614671 Издательство: Неизвестно Рейтинг: Цена: 60070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book helps data scientists and cybersecurity experts on implementing the latest AI techniques in cybersecurity. Concrete and clear steps for implementing ML security systems are provided, saving you months in research and development. By the end of this book, you will be able to build defensive systems to curb cybersecurity threats.
Автор: Halder Soma, Ozdemir Sinan Название: Hands-On Machine Learning for Cybersecurity ISBN: 1788992288 ISBN-13(EAN): 9781788992282 Издательство: Неизвестно Рейтинг: Цена: 60070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book will allow readers to implement smart solutions to their existing cybersecurity products and effectively build intelligent solutions which cater to the needs of the future. By the end of this book, you will be able to build, apply, and evaluate machine learning algorithms to identify various cybersecurity potential threats.
Автор: Bertino Название: Machine Learning Techniques for Cybersecurity ISBN: 3031282582 ISBN-13(EAN): 9783031282584 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Нет в наличии. Описание: This book explores machine learning (ML) defenses against the many cyberattacks that make our workplaces, schools, private residences, and critical infrastructures vulnerable as a consequence of the dramatic increase in botnets, data ransom, system and network denials of service, sabotage, and data theft attacks. The use of ML techniques for security tasks has been steadily increasing in research and also in practice over the last 10 years. Covering efforts to devise more effective defenses, the book explores security solutions that leverage machine learning (ML) techniques that have recently grown in feasibility thanks to significant advances in ML combined with big data collection and analysis capabilities. Since the use of ML entails understanding which techniques can be best used for specific tasks to ensure comprehensive security, the book provides an overview of the current state of the art of ML techniques for security and a detailed taxonomy of security tasks and corresponding ML techniques that can be used for each task. It also covers challenges for the use of ML for security tasks and outlines research directions. While many recent papers have proposed approaches for specific tasks, such as software security analysis and anomaly detection, these approaches differ in many aspects, such as with respect to the types of features in the model and the dataset used for training the models. In a way that no other available work does, this book provides readers with a comprehensive view of the complex area of ML for security, explains its challenges, and highlights areas for future research. This book is relevant to graduate students in computer science and engineering as well as information systems studies, and will also be useful to researchers and practitioners who work in the area of ML techniques for security tasks.
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