Strengthening Deep Neural Networks

Strengthening Deep Neural Networks PDF
Author: Katy Warr
Publisher: O'Reilly Media
ISBN: 149204492X
Size: 80.48 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 246
View: 5145

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Book Description:

Strengthening Deep Neural Networks

by Katy Warr, Strengthening Deep Neural Networks Book available in PDF, EPUB, Mobi Format. Download Strengthening Deep Neural Networks books, As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately "fool" them with data that wouldn’t trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs—the algorithms intrinsic to much of AI—are used daily to process image, audio, and video data. Author Katy Warr considers attack motivations, the risks posed by this adversarial input, and methods for increasing AI robustness to these attacks. If you’re a data scientist developing DNN algorithms, a security architect interested in how to make AI systems more resilient to attack, or someone fascinated by the differences between artificial and biological perception, this book is for you. Delve into DNNs and discover how they could be tricked by adversarial input Investigate methods used to generate adversarial input capable of fooling DNNs Explore real-world scenarios and model the adversarial threat Evaluate neural network robustness; learn methods to increase resilience of AI systems to adversarial data Examine some ways in which AI might become better at mimicking human perception in years to come







Machine Learning And Deep Learning In Real Time Applications

Machine Learning and Deep Learning in Real Time Applications PDF
Author: Mahrishi, Mehul
Publisher: IGI Global
ISBN: 1799830977
Size: 67.37 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 344
View: 1272

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Book Description:

Machine Learning And Deep Learning In Real Time Applications

by Mahrishi, Mehul, Machine Learning And Deep Learning In Real Time Applications Book available in PDF, EPUB, Mobi Format. Download Machine Learning And Deep Learning In Real Time Applications books, Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.







Strata Data Ai Superstream Series

Strata Data   AI Superstream Series PDF
Author: Kary Warr
Publisher:
ISBN:
Size: 41.71 MB
Format: PDF, ePub, Mobi
Category :
Languages : en
Pages :
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Book Description:

Strata Data Ai Superstream Series

by Kary Warr, Strata Data Ai Superstream Series Book available in PDF, EPUB, Mobi Format. Download Strata Data Ai Superstream Series books, This three-part series of half-day online events gives attendees an overarching perspective of key topics in data and AI today, including deep learning, data analytics, and natural language processing. Each of these areas is pushing the boundaries of what's possible with more computing power, data, and innovative algorithms. As you'll see in this instance, the world of neural networks is constantly changing, with new strategies and techniques for supervised, semisupervised, and unsupervised learning being developed and refined every day. These sessions will explore how using applied neural networks can help inform and improve your computer vision, natural language processing, audio recognition, and other machine learning and AI applications. About the presenters: Katy Warr is the author of Strengthening Deep Neural Networks: Making AI Less Susceptible to Adversarial Trickery. She's the head of AI at Roke Manor Research, one of the UK's longest established engineering research specialists in AI, cybersecurity, data science, and communications, and has over 20 years' experience developing software for middleware solutions, specializing in policies and security. Anthony Reina is a medical doctor with extensive experience in AI, neurophysiology, telemedicine, and data science. His biggest claim to fame is spending 12 years as a stay-at-home dad to his two sons while his wife served as a psychiatrist in the US Navy. His current work involves privacy-preserving distributed training for 3D convolutional neural networks in medical imaging (which is much easier than raising two teenage boys). Chris Van Pelt is a cofounder of Weights & Biases, an experiment tracking platform for deep learning. For the past 10 years, Chris has dedicated his career to optimizing ML workflows and teaching ML practitioners, making machine learning more accessible to all. He founded Figure Eight/CrowdFlower in 2009 and has also worked as a studio artist, computer scientist, and web engineer. He studied both art and computer science at Hope College. Hanlin Tang is senior director of Intel's AI Lab-an AI research and engineering group that conducts both foundational and applied ML research, builds several ML open source libraries in reinforcement learning and natural language processing, and delivers algorithms-hardware codesign. He previously led teams in computer vision and federal AI programs at Intel. He joined Intel through its acquisition of the deep learning startup Ne...







Decision And Game Theory For Security

Decision and Game Theory for Security PDF
Author: Linda Bushnell
Publisher: Springer
ISBN: 3030015548
Size: 75.51 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 638
View: 5014

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Book Description:

Decision And Game Theory For Security

by Linda Bushnell, Decision And Game Theory For Security Book available in PDF, EPUB, Mobi Format. Download Decision And Game Theory For Security books, The 28 revised full papers presented together with 8 short papers were carefully reviewed and selected from 44 submissions.Among the topical areas covered were: use of game theory; control theory; and mechanism design for security and privacy; decision making for cybersecurity and security requirements engineering; security and privacy for the Internet-of-Things; cyber-physical systems; cloud computing; resilient control systems, and critical infrastructure; pricing; economic incentives; security investments, and cyber insurance for dependable and secure systems; risk assessment and security risk management; security and privacy of wireless and mobile communications, including user location privacy; sociotechnological and behavioral approaches to security; deceptive technologies in cybersecurity and privacy; empirical and experimental studies with game, control, or optimization theory-based analysis for security and privacy; and adversarial machine learning and crowdsourcing, and the role of artificial intelligence in system security.







Practical Deep Learning For Cloud Mobile And Edge

Practical Deep Learning for Cloud  Mobile  and Edge PDF
Author: Anirudh Koul
Publisher: O'Reilly Media
ISBN: 1492034835
Size: 75.12 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 620
View: 3212

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Book Description:

Practical Deep Learning For Cloud Mobile And Edge

by Anirudh Koul, Practical Deep Learning For Cloud Mobile And Edge Book available in PDF, EPUB, Mobi Format. Download Practical Deep Learning For Cloud Mobile And Edge books, Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users







Neuronale Netze Selbst Programmieren

Neuronale Netze selbst programmieren PDF
Author: Tariq Rashid
Publisher: O'Reilly
ISBN: 3960101031
Size: 20.81 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : de
Pages : 232
View: 1191

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Book Description:

Neuronale Netze Selbst Programmieren

by Tariq Rashid, Neuronale Netze Selbst Programmieren Book available in PDF, EPUB, Mobi Format. Download Neuronale Netze Selbst Programmieren books, Neuronale Netze sind Schlüsselelemente des Deep Learning und der Künstlichen Intelligenz, die heute zu Erstaunlichem in der Lage sind. Sie sind Grundlage vieler Anwendungen im Alltag wie beispielsweise Spracherkennung, Gesichtserkennung auf Fotos oder die Umwandlung von Sprache in Text. Dennoch verstehen nur wenige, wie neuronale Netze tatsächlich funktionieren. Dieses Buch nimmt Sie mit auf eine unterhaltsame Reise, die mit ganz einfachen Ideen beginnt und Ihnen Schritt für Schritt zeigt, wie neuronale Netze arbeiten: - Zunächst lernen Sie die mathematischen Konzepte kennen, die den neuronalen Netzen zugrunde liegen. Dafür brauchen Sie keine tieferen Mathematikkenntnisse, denn alle mathematischen Ideen werden behutsam und mit vielen Illustrationen und Beispielen erläutert. Eine Kurzeinführung in die Analysis unterstützt Sie dabei. - Dann geht es in die Praxis: Nach einer Einführung in die populäre und leicht zu lernende Programmiersprache Python bauen Sie allmählich Ihr eigenes neuronales Netz mit Python auf. Sie bringen ihm bei, handgeschriebene Zahlen zu erkennen, bis es eine Performance wie ein professionell entwickeltes Netz erreicht. - Im nächsten Schritt tunen Sie die Leistung Ihres neuronalen Netzes so weit, dass es eine Zahlenerkennung von 98 % erreicht – nur mit einfachen Ideen und simplem Code. Sie testen das Netz mit Ihrer eigenen Handschrift und werfen noch einen Blick in das mysteriöse Innere eines neuronalen Netzes. - Zum Schluss lassen Sie das neuronale Netz auf einem Raspberry Pi Zero laufen. Tariq Rashid erklärt diese schwierige Materie außergewöhnlich klar und verständlich, dadurch werden neuronale Netze für jeden Interessierten zugänglich und praktisch nachvollziehbar.







Einf Hrung In Machine Learning Mit Python

Einf  hrung in Machine Learning mit Python PDF
Author: Andreas C. Müller
Publisher: O'Reilly
ISBN: 3960101120
Size: 75.86 MB
Format: PDF
Category : Computers
Languages : de
Pages : 378
View: 444

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Book Description:

Einf Hrung In Machine Learning Mit Python

by Andreas C. Müller, Einf Hrung In Machine Learning Mit Python Book available in PDF, EPUB, Mobi Format. Download Einf Hrung In Machine Learning Mit Python books, Machine Learning ist zu einem wichtigen Bestandteil vieler kommerzieller Anwendungen und Forschungsprojekte geworden, von der medizinischen Diagnostik bis hin zur Suche nach Freunden in sozialen Netzwerken. Um Machine-Learning-Anwendungen zu entwickeln, braucht es keine großen Expertenteams: Wenn Sie Python-Grundkenntnisse mitbringen, zeigt Ihnen dieses Praxisbuch, wie Sie Ihre eigenen Machine-Learning-Lösungen erstellen. Mit Python und der scikit-learn-Bibliothek erarbeiten Sie sich alle Schritte, die für eine erfolgreiche Machine-Learning-Anwendung notwendig sind. Die Autoren Andreas Müller und Sarah Guido konzentrieren sich bei der Verwendung von Machine-Learning-Algorithmen auf die praktischen Aspekte statt auf die Mathematik dahinter. Wenn Sie zusätzlich mit den Bibliotheken NumPy und matplotlib vertraut sind, hilft Ihnen dies, noch mehr aus diesem Tutorial herauszuholen. Das Buch zeigt Ihnen: - grundlegende Konzepte und Anwendungen von Machine Learning - Vor- und Nachteile weit verbreiteter maschineller Lernalgorithmen - wie sich die von Machine Learning verarbeiteten Daten repräsentieren lassen und auf welche Aspekte der Daten Sie sich konzentrieren sollten - fortgeschrittene Methoden zur Auswertung von Modellen und zum Optimieren von Parametern - das Konzept von Pipelines, mit denen Modelle verkettet und Arbeitsabläufe gekapselt werden - Arbeitsmethoden für Textdaten, insbesondere textspezifische Verarbeitungstechniken - Möglichkeiten zur Verbesserung Ihrer Fähigkeiten in den Bereichen Machine Learning und Data Science Dieses Buch ist eine fantastische, super praktische Informationsquelle für jeden, der mit Machine Learning in Python starten möchte – ich wünschte nur, es hätte schon existiert, als ich mit scikit-learn anfing! Hanna Wallach, Senior Researcher, Microsoft Research







Deep Learning With Hadoop

Deep Learning with Hadoop PDF
Author: Dipayan Dev
Publisher: Packt Publishing Ltd
ISBN: 1787121232
Size: 44.91 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 206
View: 3814

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Book Description:

Deep Learning With Hadoop

by Dipayan Dev, Deep Learning With Hadoop Book available in PDF, EPUB, Mobi Format. Download Deep Learning With Hadoop books, Build, implement and scale distributed deep learning models for large-scale datasets About This Book Get to grips with the deep learning concepts and set up Hadoop to put them to use Implement and parallelize deep learning models on Hadoop's YARN framework A comprehensive tutorial to distributed deep learning with Hadoop Who This Book Is For If you are a data scientist who wants to learn how to perform deep learning on Hadoop, this is the book for you. Knowledge of the basic machine learning concepts and some understanding of Hadoop is required to make the best use of this book. What You Will Learn Explore Deep Learning and various models associated with it Understand the challenges of implementing distributed deep learning with Hadoop and how to overcome it Implement Convolutional Neural Network (CNN) with deeplearning4j Delve into the implementation of Restricted Boltzmann Machines (RBM) Understand the mathematical explanation for implementing Recurrent Neural Networks (RNN) Get hands on practice of deep learning and their implementation with Hadoop. In Detail This book will teach you how to deploy large-scale dataset in deep neural networks with Hadoop for optimal performance. Starting with understanding what deep learning is, and what the various models associated with deep neural networks are, this book will then show you how to set up the Hadoop environment for deep learning. In this book, you will also learn how to overcome the challenges that you face while implementing distributed deep learning with large-scale unstructured datasets. The book will also show you how you can implement and parallelize the widely used deep learning models such as Deep Belief Networks, Convolutional Neural Networks, Recurrent Neural Networks, Restricted Boltzmann Machines and autoencoder using the popular deep learning library deeplearning4j. Get in-depth mathematical explanations and visual representations to help you understand the design and implementations of Recurrent Neural network and Denoising AutoEncoders with deeplearning4j. To give you a more practical perspective, the book will also teach you the implementation of large-scale video processing, image processing and natural language processing on Hadoop. By the end of this book, you will know how to deploy various deep neural networks in distributed systems using Hadoop. Style and approach This book takes a comprehensive, step-by-step approach to implement efficient deep learning models on Hadoop. It starts from the basics and builds the readers' knowledge as they strengthen their understanding of the concepts. Practical examples are included in every step of the way to supplement the theory.







Neural Network Projects With Python

Neural Network Projects with Python PDF
Author: James Loy
Publisher: Packt Publishing Ltd
ISBN: 1789133319
Size: 39.43 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 308
View: 1991

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Book Description:

Neural Network Projects With Python

by James Loy, Neural Network Projects With Python Book available in PDF, EPUB, Mobi Format. Download Neural Network Projects With Python books, Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key Features Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI Build expert neural networks in Python using popular libraries such as Keras Includes projects such as object detection, face identification, sentiment analysis, and more Book Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn Learn various neural network architectures and its advancements in AI Master deep learning in Python by building and training neural network Master neural networks for regression and classification Discover convolutional neural networks for image recognition Learn sentiment analysis on textual data using Long Short-Term Memory Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.







Menschheit 2 0

Menschheit 2 0 PDF
Author: Ray Kurzweil
Publisher: Lola Books
ISBN: 3944203135
Size: 65.78 MB
Format: PDF, ePub
Category : Technology & Engineering
Languages : de
Pages : 672
View: 3140

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Book Description:

Menschheit 2 0

by Ray Kurzweil, Menschheit 2 0 Book available in PDF, EPUB, Mobi Format. Download Menschheit 2 0 books, Das Jahr 2045 markiert einen historischen Meilenstein: Es ist das Jahr, in dem der Mensch seine biologischen Begrenzungen mithilfe der Technik überwinden wird. Diese als technologische Singularität bekannt gewordene Revolution wird die Menschheit für immer verändern. Googles Chefingenieur Ray Kurzweil, dessen wahnwitzigen Visionen in den vergangenen Jahrzehnten immer wieder genau ins Schwarze trafen, zeichnet in diesem Klassiker des Transhumanismus mit beispielloser Detailwut eine bunt schillernde Momentaufnahme der technischen Evolution und legt dar, weshalb diese so bald kein Ende finden, sondern im Gegenteil immer weiter an Dynamik gewinnen wird. Daraus ergibt sich eine ebenso faszinierende wie schockierende Vision für die Zukunft der Menschheit.