https://github.com/imsanjoykb/credit-card-fraud-detection
Credit Card Fraud Detection
https://github.com/imsanjoykb/credit-card-fraud-detection
credit-card-fraud-detection data-science data-visualization deep-learning machine-learning neural-network
Last synced: 19 days ago
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Credit Card Fraud Detection
- Host: GitHub
- URL: https://github.com/imsanjoykb/credit-card-fraud-detection
- Owner: imsanjoykb
- License: mit
- Created: 2020-09-09T03:10:33.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2024-04-22T06:37:44.000Z (over 1 year ago)
- Last Synced: 2025-04-09T13:01:41.449Z (7 months ago)
- Topics: credit-card-fraud-detection, data-science, data-visualization, deep-learning, machine-learning, neural-network
- Language: Jupyter Notebook
- Homepage:
- Size: 65 MB
- Stars: 38
- Watchers: 2
- Forks: 15
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Credit Card Fraud Detection
Author : Sanjoy Biswas
Email : sanjoy.eee32@gmail.com
Linkedin : [Sanjoy Biswas](https://www.linkedin.com/in/imsanjoykb/)
This is a Kaggle Credit Card Fraud Detection : Anonymized credit card transactions labeled as fraudulent or genuine - [Credit Card Fraud Detection](https://www.kaggle.com/mlg-ulb/creditcardfraud). The objective of the project is to perform data visulalization techniques to understand the insight of the data. Machine learning often required to getting the understanding of the data and its insights. This project aims apply various [Python](https://www.python.org/) tools to get a visual understanding of the data and clean it to make it ready to apply machine learning opertation on it.
## Installation
This is a Jupyter notebook. Package requirements are included in requirement.txt. This project uses Python 3.5.
Run the following command in terminal to install the required packages.
`pip3 install -r requirements.txt`
## Usage
The notebook includes all the markdowns which explain the process.
## Contributing
1. Fork it!
2. Create your feature branch: `git checkout -b my-new-feature`
3. Commit your changes: `git commit -am 'Add some feature'`
4. Push to the branch: `git push origin my-new-feature`