Dummy Level 2 report, which i have to update

Task 7: Anomaly Detection

Anomaly Detection is a good algorithm to identify a set of anomalies/those points that show unusual behavior, different from the usual behavior of the normal dataset. It maybe done in 2 different ways:

• Supervised Learning (containing labeled data)
• Unsupervised Learning(containing unlabeled data) Further, I got different insights regarding the following algorithms that get the work done:

1. Local Outlier Factor
2. Isolation Forest
3. Support Vector Machines
4. Elliptical Envelope Following would be my Kaggle notebook:

Task 8: Generative AI Task Using GAN

For now, I have a blog that I am still working on, whose link is the following: GAN

I shall soon implement the same and upload it on my report as well.