Curriculum

  1. 1

    Book Preview

    1. Ultimate Deepfake Detection Using Python Free preview
  2. 2

    Introduction

    1. (Included in full purchase)
  3. 3

    Chapter 1 : Introduction to Generative AI and Deepfake Technology

    1. (Included in full purchase)
  4. 4

    Chapter 2 : Deepfake Detection Principles and Challenges

    1. (Included in full purchase)
  5. 5

    Chapter 3 : Ethical Considerations with the Use of Deepfakes

    1. (Included in full purchase)
  6. 6

    Chapter 4 : Setting Up your Machine for Deepfake Detection using Python

    1. (Included in full purchase)
  7. 7

    Chapter 5 : Deepfake Datasets

    1. (Included in full purchase)
  8. 8

    Chapter 6 : Techniques for Deepfake Detection

    1. (Included in full purchase)
  9. 9

    Chapter 7 : Detection of Deepfake Images

    1. (Included in full purchase)
  10. 10

    Chapter 8 : Detection of Deepfake Video

    1. (Included in full purchase)
  11. 11

    Chapter 9 : Detection of Deepfake Audio

    1. (Included in full purchase)
  12. 12

    Chapter 10 : Case Study in Deepfake Detection

    1. (Included in full purchase)
  13. 13

    INDEX

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About the course

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.

About the Author

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.