CreditCardFraudDetection

Dataset used: https://www.kaggle.com/mlg-ulb/creditcardfraud/

Participants are encouraged to explore the dataset on their own and apply classification algorithm(s) which they seem appropriate. A starter Jupyter Notebook is provided for participants to kick start their analysis. Participants are encouraged to perform exploratory analysis of data before jumping on to algorithms to classify.

Quick Start:

• Fork and Clone this repo using the following command:

$ git clone https://github.com/<username>/CreditCardFraudDetection.git
$ cd CreditCardFraudDetection/Notebooks/

• Make a copy of FraudDetection.ipynb and rename it as FraudDetection-x.ipynb (where x is unique for each participant).
• Stage your changes, commit, and push using the following commands:

$ git add .
$ git commit -m "<commit message>"
$ git push origin

• Once you are satisfied with your work, create a Pull Request (PR) on the BX-GY branch of this repository. (where X stands for batch number and Y stands for group number alloted to each participant).

• Example a participant of Batch 1 Group 2 has been alloted the number 3.

  • The participant must name the file as FraudDetection-3.ipynb
  • The participant must work on his/her fork.
  • Once satisfied, the participant will create a PR on the B1-G2 branch of this repository.

Resources:

TensorFlow 2.x documentation

Tutorials by TensorFlow

Micro Courses by Kaggle

How To Use Git: A Git Cheat Sheet