Ultimate Deepfake Detection Using Python Master Deep Learning Techniques Like Cnns Gans And Transformers To Detect Deepfakes In Images Audio And Videos Using Python
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Ultimate Deepfake Detection Using Python Master Deep Learning Techniques Like Cnns Gans And Transformers To Detect Deepfakes In Images Audio And Videos Using Python
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Author : Dr. Nimrita
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-09-21
Ultimate Deepfake Detection Using Python Master Deep Learning Techniques Like Cnns Gans And Transformers To Detect Deepfakes In Images Audio And Videos Using Python written by Dr. Nimrita and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-21 with Computers categories.
Deepfake Detection Unlocked: Python Approaches for Deepfake Images, Videos, Audio Detection. Key Features● Comprehensive and graded approach to Deepfake detection using Python and its libraries. ● Practical implementation of deepfake detection techniques using Python. ● Hands-on chapters for detecting deepfake images, videos, and audio. ● Covers Case study for providing real-world application of deepfake detection. Book DescriptionIn today's digital world, mastering deepfake detection is crucial, with deepfake content increasing by 900% since 2019 and 96% used for malicious purposes like fraud and disinformation. "Ultimate Deepfake Detection with Python" equips you with the skills to combat this threat using Python’s AI libraries, offering practical tools to protect digital security across images, videos, and audio. This book explores generative AI and deepfakes, giving readers a clear understanding of how these technologies work and the challenges of detecting them. With practical Python code examples, it provides the tools necessary for effective deepfake detection across media types like images, videos, and audio. Each chapter covers vital topics, from setting up Python environments to using key datasets and advanced deep learning techniques. Perfect for researchers, developers, and cybersecurity professionals, this book enhances technical skills and deepens awareness of the ethical issues around deepfakes. Whether building new detection systems or improving current ones, this book offers expert strategies to stay ahead in digital media security. What you will learn ● Understand the fundamentals of generative AI and deepfake technology and the potential risks they pose. ● Explore the various methods and techniques used to identify deepfakes, as well as the obstacles faced in this field. ● Learn to use essential datasets and label image, video, and audio data for building deepfake detection models ● Apply advanced machine learning models like CNNs, RNNs, GANs, and Transformers for deepfake detection ● Master active and passive methods for detecting face manipulation and build CNN-based image detection systems ● Detect manipulations in videos, develop a detection system, and evaluate its performance using key metrics ● Build and implement a practical deepfake detection system to understand how these techniques are applied in real-world scenarios. Table of Contents1. Introduction to Generative AI and Deepfake Technology 2. Deepfake Detection Principles and Challenges 3. Ethical Considerations with the Use of Deepfakes 4. Setting Up your Machine for Deepfake Detection using Python 5. Deepfake Datasets 6. Techniques for Deepfake Detection 7. Detection of Deepfake Images 8. Detection of Deepfake Video 9. Detection of Deepfake Audio 10. Case Study in Deepfake Detection Index
Ultimate Deepfake Detection Using Python
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Author : Dr. Nimrita Koul
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-09-21
Ultimate Deepfake Detection Using Python written by Dr. Nimrita Koul and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-21 with Computers categories.
TAGLINE Deepfake Detection Unlocked: Python Approaches for Deepfake Images, Videos, Audio Detection. KEY FEATURES ● Comprehensive and graded approach to Deepfake detection using Python and its libraries. ● Practical implementation of deepfake detection techniques using Python. ● Hands-on chapters for detecting deepfake images, videos, and audio. ● Covers Case study for providing real-world application of deepfake detection. DESCRIPTION In today's digital world, mastering deepfake detection is crucial, with deepfake content increasing by 900% since 2019 and 96% used for malicious purposes like fraud and disinformation. "Ultimate Deepfake Detection with Python" equips you with the skills to combat this threat using Python’s AI libraries, offering practical tools to protect digital security across images, videos, and audio. This book explores generative AI and deepfakes, giving readers a clear understanding of how these technologies work and the challenges of detecting them. With practical Python code examples, it provides the tools necessary for effective deepfake detection across media types like images, videos, and audio. Each chapter covers vital topics, from setting up Python environments to using key datasets and advanced deep learning techniques. Perfect for researchers, developers, and cybersecurity professionals, this book enhances technical skills and deepens awareness of the ethical issues around deepfakes. Whether building new detection systems or improving current ones, this book offers expert strategies to stay ahead in digital media security. WHAT WILL YOU LEARN ● Understand the fundamentals of generative AI and deepfake technology and the potential risks they pose. ● Explore the various methods and techniques used to identify deepfakes, as well as the obstacles faced in this field. ● Learn to use essential datasets and label image, video, and audio data for building deepfake detection models. ● Apply advanced machine learning models like CNNs, RNNs, GANs, and Transformers for deepfake detection. ● Master active and passive methods for detecting face manipulation and build CNN-based image detection systems. ● Detect manipulations in videos, develop a detection system, and evaluate its performance using key metrics. ● Build and implement a practical deepfake detection system to understand how these techniques are applied in real-world scenarios. WHO IS THIS BOOK FOR? This book is tailored for anyone interested in deepfake detection using Python. Whether you're a researcher, developer, or cybersecurity professional, this guide provides the essential knowledge and skills. A basic understanding of Python and machine learning is helpful, but no prior experience in deepfakes is required. TABLE OF CONTENTS 1. Introduction to Generative AI and Deepfake Technology 2. Deepfake Detection Principles and Challenges 3. Ethical Considerations with the Use of Deepfakes 4. Setting Up your Machine for Deepfake Detection using Python 5. Deepfake Datasets 6. Techniques for Deepfake Detection 7. Detection of Deepfake Images 8. Detection of Deepfake Video 9. Detection of Deepfake Audio 10. Case Study in Deepfake Detection Index
Deep Learning With Python
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Author : Nikhil Ketkar
language : en
Publisher: Apress
Release Date : 2021-04-10
Deep Learning With Python written by Nikhil Ketkar and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-10 with Computers categories.
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook’s Artificial Intelligence Research Group. You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks, recurrent neural networks, long short-term memory networks, autoencoders and generative adversarial networks. Backed by a number of tricks of the trade for training and optimizing deep learning models, this edition of Deep Learning with Python explains the best practices in taking these models to production with PyTorch. What You'll Learn Review machine learning fundamentals such as overfitting, underfitting, and regularization. Understand deep learning fundamentals such as feed-forward networks, convolution neural networks, recurrent neural networks, automatic differentiation, and stochastic gradient descent. Apply in-depth linear algebra with PyTorch Explore PyTorch fundamentals and its building blocks Work with tuning and optimizing models Who This Book Is For Beginners with a working knowledge of Python who want to understand Deep Learning in a practical, hands-on manner.
An Intuitive Exploration Of Artificial Intelligence
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Author : Simant Dube
language : en
Publisher: Springer Nature
Release Date : 2021-06-21
An Intuitive Exploration Of Artificial Intelligence written by Simant Dube and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-21 with Computers categories.
This book develops a conceptual understanding of Artificial Intelligence (AI), Deep Learning and Machine Learning in the truest sense of the word. It is an earnest endeavor to unravel what is happening at the algorithmic level, to grasp how applications are being built and to show the long adventurous road in the future. An Intuitive Exploration of Artificial Intelligence offers insightful details on how AI works and solves problems in computer vision, natural language understanding, speech understanding, reinforcement learning and synthesis of new content. From the classic problem of recognizing cats and dogs, to building autonomous vehicles, to translating text into another language, to automatically converting speech into text and back to speech, to generating neural art, to playing games, and the author's own experience in building solutions in industry, this book is about explaining how exactly the myriad applications of AI flow out of its immense potential. The book is intended to serve as a textbook for graduate and senior-level undergraduate courses in AI. Moreover, since the book provides a strong geometrical intuition about advanced mathematical foundations of AI, practitioners and researchers will equally benefit from the book.
Fundamentals Of Deep Learning
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Author : Nikhil Buduma
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-05-25
Fundamentals Of Deep Learning written by Nikhil Buduma and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-25 with Computers categories.
With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning
Lear
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Author : Edward Bond
language : en
Publisher: A&C Black
Release Date : 2013-11-12
Lear written by Edward Bond and has been published by A&C Black this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-12 with Drama categories.
Edward Bond's version of Lear's story embraces myth and reality, war and politics, to reveal the violence endemic in all unjust societies. He exposes corrupted innocence as the core of social morality, and this false morality as a source of the aggressive tension which must ultimately destroy that society. In a play in which blindness becomes a dramatic metaphor for insight, Bond warns that 'it is so easy to subordinate justice to power, but when this happens power takes on the dynamics and dialectics of aggression, and then nothing is really changed'.
Developing The Curriculum
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Author : William Gordon (II)
language : en
Publisher:
Release Date : 2018
Developing The Curriculum written by William Gordon (II) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Education categories.
For undergraduate and graduate-level introductory courses in Curriculum Development, grades K-12. A practical, step-by-step guide of the entire curriculum development process Developing the Curriculum guides readers through all of the aspects of developing a curriculum--from the underlying principles and concepts to the roles of school personnel, the components of the process, uses of technology, and current issues that are shaping the field. The textbook includes both traditional and contemporary approaches to give readers a comprehensive, balanced look at the theories and evidence-based practices demonstrated to be effective curriculum specialists and instructional leaders. Now featuring a new lead author and co-author, the 9th Edition keeps readers up to date on the continually evolving field of curriculum development. A revised chapter on emerging digital trends helps future educational administrators understand how to incorporate online learning innovations into the curriculum. Updated content, research, and practices throughout reflect the current environment of rigorous standards implementation and accountability for student learning outcomes. These new features have lead to this text's nomination for the Writing and Research Award from the American Association of College for Teacher Educations (AACTE).
The Deep Learning Revolution
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Author : Terrence J. Sejnowski
language : en
Publisher: MIT Press
Release Date : 2018-10-23
The Deep Learning Revolution written by Terrence J. Sejnowski and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-23 with Computers categories.
Explore how deep learning—from Google Translate and Siri to driverless cars—is changing our lives and transforming every sector of the economy. “An important and timely book, written by a gifted scientist at the cutting edge of the AI revolution.” —Nature The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
Domain Specific Languages
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Author : Martin Fowler
language : en
Publisher: Addison-Wesley Signature Serie
Release Date : 2011
Domain Specific Languages written by Martin Fowler and has been published by Addison-Wesley Signature Serie this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.
The topics covered include.
Artificial Neural Networks In Real Life Applications
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Author : Juan Ramon Rabunal
language : en
Publisher: IGI Global
Release Date : 2006-01-01
Artificial Neural Networks In Real Life Applications written by Juan Ramon Rabunal and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-01 with Technology & Engineering categories.
"This book offers an outlook of the most recent works at the field of the Artificial Neural Networks (ANN), including theoretical developments and applications of systems using intelligent characteristics for adaptability"--Provided by publisher.