Payment Fraud Detection using Deep Learning

[AgrawalTitiksha]

Pull Request for DL-Simplified 💡

Issue Title : Payment Fraud Detection using Deep Learning

• Info about the related issue (Aim of the project) : Creating a ML project to detect any fraud in the online payments/transactions to secure the bank and users.
• Name: Titiksha Agrawal
• GitHub ID: 117917014
• Email ID: agrawaltn2311@gmail.com
• Idenitfy yourself: (Mention in which program you are contributing in. Eg. For a JWOC 2022 participant it's, JWOC Participant) Contributor SWOC S4

Closes: #386

Describe the add-ons or changes you've made 📃

As mentioned in the approach, firstly I'd loaded the dataset, preprocessed it, visualized the data to gather some insights. Then moving forward, trained it on our models viz., single input neural network, multi input neural network, and Long short term model (RNN) and achieved accuracies up to 99.93%. Our model was well successfully trained.

Type of change ☑️

What sort of change have you made:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

How Has This Been Tested? ⚙️

To test the models:
Our test dataset's accuracy was tested on the most accurate model viz., LSTM model, it gave accuracy of 99.93 %.

Checklist: ☑️

• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added things that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

[github-actions]

Our team will soon review your PR. Thanks @AgrawalTitiksha :)

[abhisheks008]

Add the EDA results/images in the README file under the Visualization tag.
@AgrawalTitiksha

[AgrawalTitiksha]

made the required changes, please recheck it

[abhisheks008]

Approved under SWOC S4 @AgrawalTitiksha