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izam-mohammed
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Wine-Quality-Prediction
connected to https://github.com/izam-mohammed/Wine-Quality-Prediction.git

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dvc.yaml 1.3 KB
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  1. stages:
    2. 

  2.   data_ingestion:
    3. 

  3.     cmd: python src/mlProject/pipeline/stage_01_data_ingestion.py
    4. 

  4.     deps:
    5. 

  5.       - src/mlProject/pipeline/stage_01_data_ingestion.py
    6. 

  6.       - config/config.yaml
    7. 

  7.     outs:
    8. 

  8.       - artifacts/data_ingestion
    9. 

  9. 

  10.   data_validation:
    11. 

  11.     cmd: python src/mlProject/pipeline/stage_02_data_validation.py
    12. 

  12.     deps:
    13. 

  13.       - src/mlProject/pipeline/stage_02_data_validation.py 
    14. 

  14.       - config/config.yaml
    15. 

  15.       - schema.yaml
    16. 

  16.     outs:
    17. 

  17.       - artifacts/data_validation
    18. 

  18. 

  19.   data_transformation:
    20. 

  20.     cmd: python src/mlProject/pipeline/stage_03_data_transformation.py
    21. 

  21.     deps:
    22. 

  22.       - src/mlProject/pipeline/stage_03_data_transformation.py
    23. 

  23.       - config/config.yaml
    24. 

  24.       - artifacts/data_ingestion
    25. 

  25.     outs:
    26. 

  26.       - artifacts/data_transformation
    27. 

  27. 

  28.   model_training:
    29. 

  29.     cmd: python src/mlProject/pipeline/stage_04_model_trainer.py
    30. 

  30.     deps:
    31. 

  31.       - src/mlProject/pipeline/stage_04_model_trainer.py
    32. 

  32.       - config/config.yaml
    33. 

  33.       - artifacts/data_transformation
    34. 

  34.     params:
    35. 

  35.       - ElasticNet
    36. 

  36.     outs:
    37. 

  37.       - artifacts/model_trainer
    38. 

  38. 

  39.   model_evaluation:
    40. 

  40.     cmd: python src/mlProject/pipeline/stage_05_model_evaluation.py
    41. 

  41.     deps:
    42. 

  42.       - src/mlProject/pipeline/stage_05_model_evaluation.py
    43. 

  43.       - config/config.yaml
    44. 

  44.       - artifacts/model_trainer
    45. 

  45.       - artifacts/data_transformation
    46. 

  46.     outs:
    47. 

  47.       - artifacts/model_evaluation
    48.
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Integrate AWS S3
Use S3 remote
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Integrate Google Cloud Storage
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Service Account Key

Congratulations!

Wine-Quality-Prediction is now integrated with Google Cloud Storage!

Delete Storage Key

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Integrate Azure Cloud Storage
Use Azure Storage
Select bucket
Set key
Finish

Use Azure Cloud Storage!

Browsing data directories saved to Azure Cloud Storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your Azure Storage bucket

Access key (If needed)

Congratulations!

Wine-Quality-Prediction is now integrated with Azure Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate S3 compatible storage
Use S3 like remote
Select bucket
Access key
Finish

Use any S3 compatible storage!

Browsing data directories saved to S3 compatible storage is possible with DAGsHub. Let's configure your repository to easily display your data in the context of any commit!

Specify your S3 bucket

Bucket name cannot be the same as the repository name. Please change one of them.

Access key (If needed)

Congratulations!

Wine-Quality-Prediction is now integrated with your S3 compatible storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes