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Malware Analysis Using Artificial Intelligence and Deep Learning, Stamp Mark, Alazab Mamoun, Shalaginov Andrii


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Автор: Stamp Mark, Alazab Mamoun, Shalaginov Andrii
Название:  Malware Analysis Using Artificial Intelligence and Deep Learning
Перевод названия: Марк Стэмп, Мармун Алазаб, Андрили Шалагинов: Анализ неисправного оборудования с использованием иску
ISBN: 9783030625818
Издательство: Springer
Классификация:



ISBN-10: 3030625818
Обложка/Формат: Hardcover
Страницы: 651
Вес: 1.11 кг.
Дата издания: 04.02.2021
Язык: English
Издание: 1st ed. 2021
Иллюстрации: 209 illustrations, color; 44 illustrations, black and white; xx, 651 p. 253 illus., 209 illus. in color.
Размер: 23.39 x 15.60 x 3.66 cm
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis.


Detection of Intrusions and Malware, and Vulnerability Assessment

Автор: Roberto Perdisci; Cl?mentine Maurice; Giorgio Giac
Название: Detection of Intrusions and Malware, and Vulnerability Assessment
ISBN: 3030220370 ISBN-13(EAN): 9783030220372
Издательство: Springer
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Цена: 10340.00 р.
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Описание: This book constitutes the proceedings of the 16th International Conference on Detection of Intrusions and Malware, and Vulnerability Assessment, DIMVA 2019, held in Gothenburg, Sweden, in June 2019. The 23 full papers presented in this volume were carefully reviewed and selected from 80 submissions.

Python Machine Learning: The Complete Beginners Guide to Programming and Deep Learning, Data Science and Artificial Intelligence Using Scikit-L

Автор: Kevin Howey
Название: Python Machine Learning: The Complete Beginners Guide to Programming and Deep Learning, Data Science and Artificial Intelligence Using Scikit-L
ISBN: 1802282076 ISBN-13(EAN): 9781802282078
Издательство: Неизвестно
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Цена: 3447.00 р.
Наличие на складе: Нет в наличии.

Описание:

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Data Management in Machine Learning Systems

Автор: Matthias Boehm, Arun Kumar, Jun Yang
Название: Data Management in Machine Learning Systems
ISBN: 1681734982 ISBN-13(EAN): 9781681734989
Издательство: Mare Nostrum (Eurospan)
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Цена: 13167.00 р.
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Описание: Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scalable manner. Data management is at the heart of many ML systems due to data-driven application characteristics, data-centric workload characteristics, and system architectures inspired by classical data management techniques. In this book, we follow this data-centric view of ML systems and aim to provide a comprehensive overview of data management in ML systems for the end-to-end data science or ML lifecycle. We review multiple interconnected lines of work: (1) ML support in database (DB) systems, (2) DB-inspired ML systems, and (3) ML lifecycle systems. Covered topics include: in-database analytics via query generation and user-defined functions, factorized and statistical-relational learning; optimizing compilers for ML workloads; execution strategies and hardware accelerators; data access methods such as compression, partitioning and indexing; resource elasticity and cloud markets; as well as systems for data preparation for ML, model selection, model management, model debugging, and model serving. Given the rapidly evolving field, we strive for a balance between an up-to-date survey of ML systems, an overview of the underlying concepts and techniques, as well as pointers to open research questions. Hence, this book might serve as a starting point for both systems researchers and developers.

Machine Learning And Artificial Intelligence In Geosciences,61

Автор: Moseley, Benjamin
Название: Machine Learning And Artificial Intelligence In Geosciences,61
ISBN: 0128216697 ISBN-13(EAN): 9780128216699
Издательство: Elsevier Science
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Цена: 27791.00 р.
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Описание: Advances in Geophysics, Volume 61 - Machine Learning and Artificial Intelligence in Geosciences the latest release in this highly-respected publication in the field of geophysics, contains new chapters on a variety of topics, including Marchenko imaging, Machine learning and inversion, A review of reduced-order modelling approaches based on machine-learning and graphs for simulation of flow and transport through fractured media, and more.

The Art of Feature Engineering: Essentials for Machine Learning

Автор: Pablo Duboue
Название: The Art of Feature Engineering: Essentials for Machine Learning
ISBN: 1108709389 ISBN-13(EAN): 9781108709385
Издательство: Cambridge Academ
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Цена: 6970.00 р.
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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.

The Promise of Artificial Intelligence: Reckoning and Judgment

Автор: Smith Brian Cantwell
Название: The Promise of Artificial Intelligence: Reckoning and Judgment
ISBN: 0262043041 ISBN-13(EAN): 9780262043045
Издательство: MIT Press
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Цена: 4224.00 р.
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Описание: An argument that--despite dramatic advances in the field--artificial intelligence is nowhere near developing systems that are genuinely intelligent.

In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability "reckoning," and argues that it does not lead to full human judgment--dispassionate, deliberative thought grounded in ethical commitment and responsible action.

Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins ("good old-fashioned AI," or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself--what sort humans have, and what sort AI aims at.

Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.

Robotics Through Science Fiction: Artificial Intelligence Explained Through Six Classic Robot Short Stories

Автор: Murphy Robin R.
Название: Robotics Through Science Fiction: Artificial Intelligence Explained Through Six Classic Robot Short Stories
ISBN: 0262536269 ISBN-13(EAN): 9780262536264
Издательство: MIT Press
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Цена: 2772.00 р.
Наличие на складе: Нет в наличии.

Описание:

Six classic science fiction stories and commentary that illustrate and explain key algorithms or principles of artificial intelligence.

This book presents six classic science fiction stories and commentary that illustrate and explain key algorithms or principles of artificial intelligence. Even though all the stories were originally published before 1973, they help readers grapple with two questions that stir debate even today: how are intelligent robots programmed? and what are the limits of autonomous robots? The stories--by Isaac Asimov, Vernor Vinge, Brian Aldiss, and Philip K. Dick--cover telepresence, behavior-based robotics, deliberation, testing, human-robot interaction, the "uncanny valley," natural language understanding, machine learning, and ethics. Each story is preceded by an introductory note, "As You Read the Story," and followed by a discussion of its implications, "After You Have Read the Story." Together with the commentary, the stories offer a nontechnical introduction to robotics. The stories can also be considered as a set of--admittedly fanciful--case studies to be read in conjunction with more serious study.

Contents
"Stranger in Paradise" by Isaac Asimov, 1973
"Runaround" by Isaac Asimov, 1942
"Long Shot" by Vernor Vinge, 1972
"Catch That Rabbit" by Isaac Asimov, 1944
"Super-Toys Last All Summer Long" by Brian Aldiss, 1969
"Second Variety" by Philip K. Dick, 1953

Multi-Objective Optimization using Artificial Intelligence Techniques

Автор: Seyedali Mirjalili; Jin Song Dong
Название: Multi-Objective Optimization using Artificial Intelligence Techniques
ISBN: 3030248348 ISBN-13(EAN): 9783030248345
Издательство: Springer
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Цена: 8384.00 р.
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Описание: This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.

The AI Advantage: How to Put the Artificial Intelligence Revolution to Work

Автор: Davenport Thomas H.
Название: The AI Advantage: How to Put the Artificial Intelligence Revolution to Work
ISBN: 0262039176 ISBN-13(EAN): 9780262039178
Издательство: MIT Press
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Цена: 2772.00 р.
Наличие на складе: Нет в наличии.

Описание:

How businesses can put artificial intelligence to work now: a guide to available technologies, the tasks they can do, and practical AI business strategy,

In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence--also known as cognitive technologies--in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze--remember when it seemed plausible that IBM's Watson could cure cancer?--to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the "moonshot" (curing cancer, or synthesizing all investment knowledge); look for the "low-hanging fruit" to make your company more efficient.

Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed--important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning ("analytics on steroids"), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise.

Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI.

Machine Learning for Future Wireless Communications

Автор: Fa–Long Luo
Название: Machine Learning for Future Wireless Communications
ISBN: 1119562252 ISBN-13(EAN): 9781119562252
Издательство: Wiley
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Цена: 18683.00 р.
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Описание:

A comprehensive review to the theory, application and research of machine learning for future wireless communications

In one single volume, Machine Learning for Future Wireless Communications provides a comprehensive and highly accessible treatment to the theory, applications and current research developments to the technology aspects related to machine learning for wireless communications and networks. The technology development of machine learning for wireless communications has grown explosively and is one of the biggest trends in related academic, research and industry communities.

Deep neural networks-based machine learning technology is a promising tool to attack the big challenge in wireless communications and networks imposed by the increasing demands in terms of capacity, coverage, latency, efficiency flexibility, compatibility, quality of experience and silicon convergence. The author - a noted expert on the topic - covers a wide range of topics including system architecture and optimization, physical-layer and cross-layer processing, air interface and protocol design, beamforming and antenna configuration, network coding and slicing, cell acquisition and handover, scheduling and rate adaption, radio access control, smart proactive caching and adaptive resource allocations. Uniquely organized into three categories: Spectrum Intelligence, Transmission Intelligence and Network Intelligence, this important resource:

  • Offers a comprehensive review of the theory, applications and current developments of machine learning for wireless communications and networks
  • Covers a range of topics from architecture and optimization to adaptive resource allocations
  • Reviews state-of-the-art machine learning based solutions for network coverage
  • Includes an overview of the applications of machine learning algorithms in future wireless networks
  • Explores flexible backhaul and front-haul, cross-layer optimization and coding, full-duplex radio, digital front-end (DFE) and radio-frequency (RF) processing

Written for professional engineers, researchers, scientists, manufacturers, network operators, software developers and graduate students, Machine Learning for Future Wireless Communications presents in 21 chapters a comprehensive review of the topic authored by an expert in the field.

Deep Learning Techniques and Optimization Strategies in Big Data Analytics

Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed,
Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics
ISBN: 1799811921 ISBN-13(EAN): 9781799811923
Издательство: Mare Nostrum (Eurospan)
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Цена: 35897.00 р.
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Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.

Deep Learning For Eeg-based Brain-computer Interfaces: Representations, Algorithms And Applications

Автор: Lina Yao, Xiang Zhang
Название: Deep Learning For Eeg-based Brain-computer Interfaces: Representations, Algorithms And Applications
ISBN: 1786349582 ISBN-13(EAN): 9781786349583
Издательство: World Scientific Publishing
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Цена: 14256.00 р.
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Описание: Deep Learning for EEG-based Brain-Computer Interfaces is an exciting book that describes how emerging deep learning improves the future development of Brain-Computer Interfaces (BCI).


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