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A fully functional end to end ML application integrating ML flow, Docker and cloud

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Raghucharan16/MLops

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workflow

  • 1.Update config.yaml
  • 2.update schema.yaml (at the time of data validation)
  • 3.update params.yaml (at the time of model training)
  • 4.update entity
  • 5.update configuration manager in scr/config
  • 6.update the components
  • 7.update the pipline
  • 8.update the main.py
  • 9.update the app.py

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A fully functional end to end ML application integrating ML flow, Docker and cloud

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