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HARSHALKUMRE
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machine-learning-pipeline

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  1. schema: '2.0'
    2. 

  2. stages:
    3. 

  3.   preprocess:
    4. 

  4.     cmd: python src/preprocess.py
    5. 

  5.     deps:
    6. 

  6.     - path: data/raw/data.csv
    7. 

  7.       hash: md5
    8. 

  8.       md5: f2906818eda8fcfc8f8416557ab1e6df
    9. 

  9.       size: 23873
    10. 

  10.     - path: src/preprocess.py
    11. 

  11.       hash: md5
    12. 

  12.       md5: 77b14a8d90296d66951b53bd3ac46a5d
    13. 

  13.       size: 507
    14. 

  14.     params:
    15. 

  15.       params.yaml:
    16. 

  16.         preprocess.input: data/raw/data.csv
    17. 

  17.         preprocess.output: data/processed/data.csv
    18. 

  18.     outs:
    19. 

  19.     - path: data/processed/data.csv
    20. 

  20.       hash: md5
    21. 

  21.       md5: bea5b9be0aee81bfecbe7100ed8b90da
    22. 

  22.       size: 23961
    23. 

  23.   train:
    24. 

  24.     cmd: python src/train.py
    25. 

  25.     deps:
    26. 

  26.     - path: data/raw/data.csv
    27. 

  27.       hash: md5
    28. 

  28.       md5: f2906818eda8fcfc8f8416557ab1e6df
    29. 

  29.       size: 23873
    30. 

  30.     - path: src/train.py
    31. 

  31.       hash: md5
    32. 

  32.       md5: af9ec505ebf475dffc7102f9746ea931
    33. 

  33.       size: 3726
    34. 

  34.     params:
    35. 

  35.       params.yaml:
    36. 

  36.         train.data: data/raw/data.csv
    37. 

  37.         train.max_depth: 5
    38. 

  38.         train.model: models/model.pkl
    39. 

  39.         train.n_estimators: 100
    40. 

  40.         train.random_state: 42
    41. 

  41.     outs:
    42. 

  42.     - path: models/model.pkl
    43. 

  43.       hash: md5
    44. 

  44.       md5: 51d85307c0ac1566e9968b532b9c2c1c
    45. 

  45.       size: 2293519
    46. 

  46.   evaluate:
    47. 

  47.     cmd: python src/evaluate.py
    48. 

  48.     deps:
    49. 

  49.     - path: data/raw/data.csv
    50. 

  50.       hash: md5
    51. 

  51.       md5: f2906818eda8fcfc8f8416557ab1e6df
    52. 

  52.       size: 23873
    53. 

  53.     - path: models/model.pkl
    54. 

  54.       hash: md5
    55. 

  55.       md5: 51d85307c0ac1566e9968b532b9c2c1c
    56. 

  56.       size: 2293519
    57. 

  57.     - path: src/evaluate.py
    58. 

  58.       hash: md5
    59. 

  59.       md5: 597f633d7aa0088bbf1d08b8309edaed
    60. 

  60.       size: 1124
    61.
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