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puneethp
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RPPP
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  1. make_data:
    2. 

  2.   cmd: python3 make_dataset.py
    3. 

  3.   deps:
    4. 

  4.   - path: make_dataset.py
    5. 

  5.     md5: d700791fac216077c43596a5ea326f74
    6. 

  6.   outs:
    7. 

  7.   - path: remote://remote-wfs/rML-raw-data.csv
    8. 

  8.     md5: 15ae93ba7e913bcad890c2461048a9c9
    9. 

  9. eval:
    10. 

  10.   cmd: python3 src/evaluate.py
    11. 

  11.   deps:
    12. 

  12.   - path: data/processed/rML-test.csv
    13. 

  13.     md5: 629a4d0505914f5599bb94be702341b5
    14. 

  14.     size: 2862132
    15. 

  15.   - path: models/model.pkl
    16. 

  16.     md5: 98f38f3ef55a5cfe9a0fb27a1f6616ae
    17. 

  17.     size: 1127
    18. 

  18.   - path: src/evaluate.py
    19. 

  19.     md5: 5f060c468f17fc53e9a57d2681cf291a
    20. 

  20.     size: 1590
    21. 

  21.   params:
    22. 

  22.     params.yaml:
    23. 

  23.       pre_process:
    24. 

  24.         chunk_size: 5000
    25. 

  25.         target_col: is_top_decile
    26. 

  26.       train:
    27. 

  27.         loss: log
    28. 

  28.         use_text_cols: false
    29. 

  29.         use_number_category_cols: true
    30. 

  30.   outs:
    31. 

  31.   - path: models/metrics/test.yaml
    32. 

  32.     md5: 85fa7115fb52ca48ffe9e8de88d3bee0
    33. 

  33.     size: 102
    34. 

  34. preprocessing:
    35. 

  35.   cmd: python3 src/preprocess.py
    36. 

  36.   deps:
    37. 

  37.   - path: data/raw/rML-raw-data.csv
    38. 

  38.     md5: ce3a47e51025812d0e5d2e5914feadb7
    39. 

  39.     size: 7361822
    40. 

  40.   - path: general_params.yml
    41. 

  41.     md5: fd72d874a18159ce4a7855eb23ce4165
    42. 

  42.     size: 44
    43. 

  43.   - path: src/preprocess.py
    44. 

  44.     md5: 6b1cf3af3a8e62805f8d81f9e1dcd559
    45. 

  45.     size: 2620
    46. 

  46.   outs:
    47. 

  47.   - path: data/processed/rML-test.csv
    48. 

  48.     md5: 629a4d0505914f5599bb94be702341b5
    49. 

  49.     size: 2862132
    50. 

  50.   - path: data/processed/rML-train.csv
    51. 

  51.     md5: 9b1f377458cc33aaa5b72a63fbb757fe
    52. 

  52.     size: 8087263
    53. 

  53. training:
    54. 

  54.   cmd: python3 src/training.py
    55. 

  55.   deps:
    56. 

  56.   - path: data/processed/rML-train.csv
    57. 

  57.     md5: 9b1f377458cc33aaa5b72a63fbb757fe
    58. 

  58.     size: 8087263
    59. 

  59.   - path: general_params.yml
    60. 

  60.     md5: fd72d874a18159ce4a7855eb23ce4165
    61. 

  61.     size: 44
    62. 

  62.   - path: src/model_def.py
    63. 

  63.     md5: f93783b7270ebd57d40f9f6c1b8e4188
    64. 

  64.     size: 2174
    65. 

  65.   - path: src/training.py
    66. 

  66.     md5: 388970c00f0c5eb6b27a9077a55584d0
    67. 

  67.     size: 871
    68. 

  68.   outs:
    69. 

  69.   - path: models/metrics/train.yaml
    70. 

  70.     md5: c4fb83687d866968d411df61c68b5d63
    71. 

  71.     size: 103
    72. 

  72.   - path: models/model.pkl
    73. 

  73.     md5: 98f38f3ef55a5cfe9a0fb27a1f6616ae
    74. 

  74.     size: 1127
    75. 

  75.   - path: params.yml
    76. 

  76.     md5: 2425d4cc306ef245b718ef1179191bf5
    77. 

  77.     size: 542
    78. 

  78. pre_process:
    79. 

  79.   cmd: python3 src/pre_process.py
    80. 

  80.   deps:
    81. 

  81.   - path: data/raw/rML-raw-data.csv
    82. 

  82.     md5: ce3a47e51025812d0e5d2e5914feadb7
    83. 

  83.     size: 7361822
    84. 

  84.   - path: src/pre_process.py
    85. 

  85.     md5: e05a7f042ab6e3f81eb27e723a9668cf
    86. 

  86.     size: 2622
    87. 

  87.   params:
    88. 

  88.     params.yaml:
    89. 

  89.       pre_process:
    90. 

  90.         chunk_size: 5000
    91. 

  91.         target_col: is_top_decile
    92. 

  92.   outs:
    93. 

  93.   - path: data/processed/rML-test.csv
    94. 

  94.     md5: 629a4d0505914f5599bb94be702341b5
    95. 

  95.     size: 2862132
    96. 

  96.   - path: data/processed/rML-train.csv
    97. 

  97.     md5: 9b1f377458cc33aaa5b72a63fbb757fe
    98. 

  98.     size: 8087263
    99. 

  99. train:
    100. 

  100.   cmd: python3 src/train.py
    101. 

  101.   deps:
    102. 

  102.   - path: data/processed/rML-train.csv
    103. 

  103.     md5: 9b1f377458cc33aaa5b72a63fbb757fe
    104. 

  104.     size: 8087263
    105. 

  105.   - path: src/model_def.py
    106. 

  106.     md5: 2f20bd7e1336a86ad3adff8b859ccffb
    107. 

  107.     size: 1985
    108. 

  108.   - path: src/train.py
    109. 

  109.     md5: 8bd59fb472442f2b7851ee1e25da45cb
    110. 

  110.     size: 750
    111. 

  111.   params:
    112. 

  112.     params.yaml:
    113. 

  113.       train:
    114. 

  114.         loss: log
    115. 

  115.         use_text_cols: false
    116. 

  116.         use_number_category_cols: true
    117. 

  117.   outs:
    118. 

  118.   - path: models/metrics/train.yaml
    119. 

  119.     md5: c4fb83687d866968d411df61c68b5d63
    120. 

  120.     size: 103
    121. 

  121.   - path: models/model.pkl
    122. 

  122.     md5: 98f38f3ef55a5cfe9a0fb27a1f6616ae
    123. 

  123.     size: 1127
    124.
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Integrate Google Cloud Storage
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Integrate Azure Cloud Storage
Use Azure Storage
Select bucket
Set key
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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!

RPPP is now integrated with Azure Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

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Yes