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: 6334.00 р. 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: 13543.00 р. 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: 16078.00 р. 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: 11179.00 р. 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.
Описание: Usable Security.- Authentication Management of Home IoT Devices.- Emics and Etics of Usable Security: Culturally Specific or Culturally Universal?.- Development of a Novice-Friendly Representation of Camouflaged Boolean Networks.- Testing Facial Recognition Software for Young Adults and Adolescents: An Integrative Review.- Eye Gaze and Interaction Differences of Holistic versus Analytic Users in Image-recognition Human Interaction Proof Schemes.- Risk Assessment of "Ostrich ZIP".- Identity Recognition based on the Hierarchical Behavior Characteristics of Network Users.- Security Analysis of Transaction Authorization Methods for Next Generation Electronic Payment Services.- Security and Privacy by Design.- Beyond Murphy's Law: Applying wider Human Factors Behavioural Science Approaches in Cyber-Security Resilience.- A Human Factor Approach to Threat Modeling.- Smart Technologies and Internet of Things Designed for Aging in Place.- Please Stop Listening while I Make a Private Call: Context-Aware In-Vehicle Mode of a Voice-Controlled Intelligent Personal Assistant with a Privacy Consideration.- Enterprise Data Sharing Requirements: Rich Policy Languages and Intuitive User Interfaces.- Heuristic Evaluation of Vulnerability Risk Management Leaders' Presentations of Cyber Threat and Cyber Risk.- Human Individual Difference Predictors in Cyber Security: Exploring an Alternative Scale Method and Data Resolution to Modelling Cyber Secure Behavior.- Privacy Design Strategies and the GDPR: A Systematic Literature Review.- User Behavior Analysis in Cybersecurity.- 'Just-in-Time' Parenting: A Two-Month Examination of the Bi-directional Influences between Parental Mediation and Adolescent Online Risk Exposure.- Understanding User Behavior, Information Exposure, and Privacy Risks in Managing Old Devices.- Perceptions of Security and Privacy in mHealth.- Understanding User's Behavior and Protection Strategy upon Losing, or Identifying Unauthorized Access to Online Account.- CyberPin - Challenges on Recognizing Youngest Cyber Talents.- It's Not My Problem: How Healthcare Models relate to SME Cybersecurity Awareness.- Understanding the Last Line of Defense: Human Response to Cybersecurity Events.- Security and Privacy Awareness.- The Effectiveness of Video Messaging Campaigns to Use 2FA.- A Study on Online Businesses' Commitment to Consumer Privacy.- Help the User Recognize a Phishing Scam: Design of Explanation Messages in Warning Interfaces for Phishing Attacks.- Social Engineering Attacks: Recent Advances and Challenges.- Brand Validation: Security Indicator to Better Indicate Website Identity.- Study on the Impact of Learning about Information Security Measures on Mental Models: Applying Cybersecurity Frameworks to Self-learning Materials.- Gaming Apps' and Social Media Partnership: A Privacy Perspective.
Автор: Kaur Название: Understanding Cybersecurity Management in FinTech ISBN: 3030799174 ISBN-13(EAN): 9783030799175 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book uncovers the idea of understanding cybersecurity management in FinTech. The book delves into understanding cyber threats and adversaries who can exploit those threats. The book helps readers understand cyber threat landscape comprising different threat categories that can exploit different types of vulnerabilties identified in FinTech.
Автор: King, Steve Название: Losing the cybersecurity war ISBN: 1032364084 ISBN-13(EAN): 9781032364087 Издательство: Taylor&Francis Рейтинг: Цена: 4592.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An explanation of the five pillars or battlefields of Cybersecurity and how a Zero Trust approach can change the advantage on each battlefield. The five battlefields include Economics, Technology, Information, Education and Leadership.
Автор: Montasari Название: Countering Cyberterrorism ISBN: 3031219198 ISBN-13(EAN): 9783031219191 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a comprehensive analysis covering the confluence of Artificial Intelligence (AI), Cyber Forensics and Digital Policing in the context of the United Kingdom (UK), United States (US) and European Union (EU) national cybersecurity. More specifically, this book explores ways in which the adoption of AI algorithms (such as Machine Learning, Deep Learning, Natural Language Processing, and Big Data Predictive Analytics (BDPAs) transforms law enforcement agencies (LEAs) and intelligence service practices. It explores the roles that these technologies play in the manufacture of security, the threats to freedom and the levels of social control in the surveillance state. This book also examines the malevolent use of AI and associated technologies by state and non-state actors. Along with this analysis, it investigates the key legal, political, ethical, privacy and human rights implications of the national security uses of AI in the stated democracies. This book provides a set of policy recommendations to help to mitigate these challenges. Researchers working in the security field as well advanced level students in computer science focused on security will find this book useful as a reference. Cyber security professionals, network security analysts, police and law enforcement agencies will also want to purchase this book.
Автор: Wu, Chwan-Hwa (John) Название: Introduction to Computer Networks and Cybersecurity ISBN: 1466572132 ISBN-13(EAN): 9781466572133 Издательство: Taylor&Francis Рейтинг: Цена: 27562.00 р. Наличие на складе: Нет в наличии.
Автор: Mclaughlin, Kevin Lynn Название: Cybersecurity operations and fusion centers ISBN: 1032194367 ISBN-13(EAN): 9781032194363 Издательство: Taylor&Francis Рейтинг: Цена: 6889.00 р. 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.
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