- Update config.yaml
- Update schema.yaml
- Update params.yaml
- Update the entity
- Update the configuration manager in src config
- Update the components
- Update the pipeline
- Update the main.py
- Update the app.py
Clone the repository
https://github.com/Mudit-Sharma-30/Ml-Project-with-ml-flow
conda create -n mlproj python=3.8 -y
conda activate mlproj
pip install -r requirements.txt
# Finally run the following command
python app.py
Now,
open up you local host and port
- mlflow ui
MLFLOW_TRACKING_URI=https://dagshub.com/Mudit-Sharma-30/Ml-Project-with-ml-flow.mlflow
MLFLOW_TRACKING_USERNAME=Mudit-Sharma-30
MLFLOW_TRACKING_PASSWORD=3625d590b439d6f0f1c25b63436532ae1dce8180
python script.py
Run this to export as env variables:
export MLFLOW_TRACKING_URI=https://dagshub.com/Mudit-Sharma-30/Ml-Project-with-ml-flow.mlflow
export MLFLOW_TRACKING_USERNAME=Mudit-Sharma-30
export MLFLOW_TRACKING_PASSWORD=3625d590b439d6f0f1c25b63436532ae1dce8180
MLflow
- Its Production Grade
- Trace all of your expriements
- Logging & tagging your model
http://muditsharma.pythonanywhere.com/