Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/vikrantdeshpande09876/credit_card_fraud_detection
Deploying Classification Model on GCP for detecting anomalous behavior in credit-card transactions. A crucial aspect for credit-card companies to recognize fraudulent activity and not charge customers for items they didn't purchase. A subtle line needs to be drawn and my main focus here is to reduce blocked-transactions of legitimate customers.
https://github.com/vikrantdeshpande09876/credit_card_fraud_detection
airflow airflow-docker data-wrangling google-cloud-functions google-cloud-platform google-cloud-storage machine-learning pandas python python-package random-forest sklearn
Last synced: 3 months ago
JSON representation
Deploying Classification Model on GCP for detecting anomalous behavior in credit-card transactions. A crucial aspect for credit-card companies to recognize fraudulent activity and not charge customers for items they didn't purchase. A subtle line needs to be drawn and my main focus here is to reduce blocked-transactions of legitimate customers.
- Host: GitHub
- URL: https://github.com/vikrantdeshpande09876/credit_card_fraud_detection
- Owner: vikrantdeshpande09876
- License: mit
- Created: 2022-01-15T06:16:48.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-03-17T14:57:51.000Z (almost 2 years ago)
- Last Synced: 2024-10-14T19:21:08.942Z (3 months ago)
- Topics: airflow, airflow-docker, data-wrangling, google-cloud-functions, google-cloud-platform, google-cloud-storage, machine-learning, pandas, python, python-package, random-forest, sklearn
- Language: Jupyter Notebook
- Homepage: https://pypi.org/project/anonymized-fraud-detection/
- Size: 41.7 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Credit Card Fraud Detection
Head on over to the [wikis](https://github.com/vikrantdeshpande09876/Credit_Card_Fraud_Detection/wiki) to know more about the entire project architecture and motivation!