😉How to run the project:

1. Create a new conda environment with the following command:

conda create -p venv python==3.9.18 -y

2.😊 Activate the conda environment with the following command:

conda activate venv/

3.✌️ Install the package requirements:

pip install -r requirements.txt

4. 😎Export the following parameters

export MLFLOW_TRACKING_USERNAME=tejas05in

export MLFLOW_TRACKING_PASSWORD=9efcb5c7b79d0e949378459b922b1462a80fa413

5. 😁Run the training pipeline to train the model and create the artifacts:

python src/pipelines/training_pipeline.py

6.🤗 Mlflow ui can be accessed by running: (Optional)

mlflow ui

7.🙌 Run:

streamlit run application.py ## initiates streamlit application

8.🤩🥳 Upload data:

Upload csv file to get the results

MLFLOW_TRACKING_URI=https://dagshub.com/Swadhin-203/Credit_Card_Default_Prediction-.mlflow

docker pull tejas05in/ccfapp

A big thank you to all the wonderful people who have contributed to this project! 🙌

• Swadhin Gyanajyoti Nayak🌟
• Tejas J 🤗
• Nihal Barhaiyya🎉