Tutorial on Anomaly Detection

[rajveer43]

Description

Create a Jupyter Notebook tutorial that implements Anomaly Detection. Explain the concept of Anomaly Detection, and its applications, and provide a tutorial on how to use it in machine learning projects.

Acceptance Criteria

• Submit a Jupyter notebook containing the tutorial and the necessary datasets if need
• Modify the README.md file to include the new tutorial and a link to the added notebook

[rashidrao-pk]

Hi @rajveer43 ,

I would like to work on this issue. I can add a beginner-friendly Jupyter Notebook tutorial on Anomaly Detection covering:

• Concept and real-world applications
• Dataset preparation
• Isolation Forest
• Local Outlier Factor
• One-Class SVM
• Evaluation using confusion matrix, classification report, and ROC-AUC
• Visualizing detected anomalies

I will also update the README.md with a link to the new notebook.

Please assign this issue to me if possible.

[rashidrao-pk]

Hi! Just a gentle follow-up on this issue. I wanted to check if there have been any updates or if there's anything else I can do to help move it forward.

I'm still happy to contribute and make any requested changes if needed. Thanks again for your time and for maintaining this awesome repository!

@rajveer43 @miriamspsantos

[rajveer43]

@rashidrao-pk you can contribute, Pick any of the problem and fix it.

[rashidrao-pk]

@rajveer43 Thanks! I actually already contributed by opening a pull request for this issue:

#42

Whenever you have time, I’d really appreciate a review. If there are any changes or improvements you’d like me to make, I’d be happy to update the PR.

Thanks again for your time and for maintaining this repository!

[rashidrao-pk]

Hi @rajveer43, just following up on PR #42, which I submitted for Issue #28. The proposed contribution is already implemented and ready for review.

Whenever you have a chance, I'd appreciate any feedback. I'm happy to make any changes needed. Thanks!