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An End-to-End production ready application for predicting the quality of wine🍇. Build ML model and deployed using flask 🤖. Used various MLOps tools to smooth the workflow.

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izam-mohammed/Wine-Quality-Prediction

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  1. Update config.yaml
  2. Update schema.yaml
  3. Update params.yaml
  4. Update the entity
  5. Update the configuration manager in src config
  6. Update the components
  7. Update the pipeline
  8. Update the main.py
  9. Update the app.py

DagsHub

MLFLOW_TRACKING_URI=https://dagshub.com/izam-mohammed/Wine-Quality-Prediction.mlflow \
MLFLOW_TRACKING_USERNAME=izam-mohammed \
MLFLOW_TRACKING_PASSWORD=f497810936eeaf4fdc502187990343255063fd53 \
python script.py

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An End-to-End production ready application for predicting the quality of wine🍇. Build ML model and deployed using flask 🤖. Used various MLOps tools to smooth the workflow.

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