Idea is to recognize fraudulent credit card transactions so that the customers of credit card companies are not charged for items that they did not purchase.
- Numpy
- Pandas
- Sklearn
- Matplotlib
- Seaborn
- The model used must be simple and fast enough to detect the anomaly and classify it as a fraudulent transaction as quickly as possible.
- Imbalance can be dealt with by properly using some methods which we will talk about in the next paragraph
- For protecting the privacy of the user the dimensionality of the data can be reduced.
- A more trustworthy source must be taken which double-check the data, at least for training the model.
- We can make the model simple and interpretable so that when the scammer adapts to it with just some tweaks we can have a new model up and running to deploy.
Ref from GEEKSFORGEEKS
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Name : Akshat Jain
University : Graphic Era University, Dehradun(UK)
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