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 (Paperback, Dr. Nimrita Koul)

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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  (Paperback, Dr. Nimrita Koul)

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Highlights
  • Binding: Paperback
  • Publisher: Orange Education Pvt. Ltd
  • Genre: Artificial Intelligence / General, Artificial Intelligence / Computer Vision & Pattern Recognition, Data Science / Neural Networks
  • ISBN: 9788197953422
  • Edition: 1, 2024
  • Pages: 286
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  • 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.
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    Specifications
    Book Details
    Publication Year
    • 2024 September
    Book Type
    • Non Fiction
    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
    Contributors
    Author Info
    • Dr. Nimrita Koul is an Associate Professor of Computer Science and Engineering at Reva University in Bangalore, Karnataka, India. With a PhD in Machine Learning and an academic and research career spanning over 19 years, she is an active researcher in the areas of Machine Learning, Natural Language Processing, and Generative AI. Dr. Koul is a senior member of IEEE and a member of ACM, and she has been the principal investigator for multiple research projects worth over 1.3 crores, funded by the Department of Science and Technology, Government of India. Her expertise has been recognized through several prestigious awards, including the Research Accelerator Award in 2021, the Jetson Nano Grant in 2020, and the IBM Generative AI Award in 2023. A passionate educator, Dr. Koul is committed to using AI to enhance education, particularly in remote and underserved areas. She has delivered numerous international workshops and seminars on Data Analysis, Machine Learning, Natural Language Processing, and Generative AI, and is a sought-after speaker at global conferences such as GHC2023 and WomenWhoConnect Forward 2021. In addition to her academic pursuits, Dr. Koul is actively involved in mentoring and inspiring the next generation of technologists, particularly women in tech, through her role as an ambassador for Google Women Techmakers. In this book, Ultimate Deepfake Detection Using Python, Dr. Koul combines her extensive knowledge of AI with practical Python programming to guide readers through the latest techniques in detecting deepfake videos. The book also explores recent advancements in the field, offering insights into the future directions of deepfake detection research.
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