Unsupervised Fraud Detection Using Variational Autoencoder (VAE) | Anomaly Detection with Dataset

Overview

This indexed tutorial covers Unsupervised Fraud Detection Using Variational Autoencoder (VAE) | Anomaly Detection with Dataset from Learn with US.

Learn how to implement unsupervised anomaly detection using a Variational Autoencoder (VAE) in PyTorch on a real-world credit ...

Watch the tutorial

Use the source video for the full walkthrough: https://www.youtube.com/watch?v=iAxPoPwR9GY

What to learn

1. Review the tutorial title and description to identify the workflow.
2. Follow along with the creator's steps in the video.
3. Pause at each major action and reproduce it in your own project.
4. Save any prompts, settings, or code snippets shown in the walkthrough.
5. Test the final result and adapt it to your use case.

Tips

• Keep the video open while you work through the steps.
• Compare your output with the creator's final result.
• Re-run the workflow with your own data or project requirements.