"Responsible AI: Build Your DeepFake Detection Engine" bootcamp for Bannari Amman Institute of Technology

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Responsible AI_ Build Your DeepFake Detection Engine 1 Click Banner
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Learning Objectives: After completing this course you will,

  • A refresher on the Basics of Computer Vision.
  • Familiarize with MTCNN and Inception-ResNet models for DeepFake detection.
  • Build a working solution that can help you detect an image as real or fake.

Complete this course in 3 easy steps to earn your certificate!

STEP 1 : Watch the below self-guided tutorial.
STEP 2 : Practice as you watch the video by installing and working with the kandi 1-click solution kit.
STEP 3 : Complete the assessment to receive your certificate.

STEP 1 : TUTORIAL

Watch this self guided tutorial on “Responsible AI: Build Your DeepFake Detection Engine”.

STEP 2 : PRACTICAL EXERCISE

Click the below button to access the DeepFake Detection Engine kandi kit. This kit has all the required dependencies and resources you need to build your application.

Click on the 1-Click Installer button on the kandi kit page to install the DeepFake Detection Engine kit. On installing and running this kit, you will have a working model that you can customize and use in your project.

kandi 1-Click Kit - Dark

STEP 3 : ASSESSMENT

Complete a short assessment and earn your certificate now. Congrats

Take Assessment

Your assessment will be reviewed and you will receive a verified certificate via email within a week.

SUPPORT

Reach out to us by replying below for any help you may need with this course.

We hope you enjoyed using kandi! Continue your learning journey with kandi Congrats

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1. Which of the following is NOT a task that can be performed using Computer Vision?

  • Object Detection
  • Image Segmentation
  • Text Recognition
  • Speech Synthesis

0 voters

3

2. What is a common challenge in face recognition?

  • Poor lighting conditions
  • Occlusion
  • Variation in pose and expression
  • All of the above

0 voters

4

3. What is PyTorch?

  • A deep learning framework
  • A programming language
  • A computer vision algorithm
  • An image processing library

0 voters