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arnab-saha
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example-get-started

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  1. schema: '2.0'
    2. 

  2. stages:
    3. 

  3.   prepare:
    4. 

  4.     cmd: python src/prepare.py data/data.xml
    5. 

  5.     deps:
    6. 

  6.     - path: data/data.xml
    7. 

  7.       md5: a304afb96060aad90176268345e10355
    8. 

  8.       size: 37891850
    9. 

  9.     - path: src/prepare.py
    10. 

  10.       md5: 285af85d794bb57e5d09ace7209f3519
    11. 

  11.       size: 1581
    12. 

  12.     params:
    13. 

  13.       params.yaml:
    14. 

  14.         prepare.seed: 20170428
    15. 

  15.         prepare.split: 0.2
    16. 

  16.     outs:
    17. 

  17.     - path: data/prepared
    18. 

  18.       md5: 20b786b6e6f80e2b3fcf17827ad18597.dir
    19. 

  19.       size: 23861319
    20. 

  20.       nfiles: 2
    21. 

  21.   featurize:
    22. 

  22.     cmd: python src/featurization.py data/prepared data/features
    23. 

  23.     deps:
    24. 

  24.     - path: data/prepared
    25. 

  25.       md5: 20b786b6e6f80e2b3fcf17827ad18597.dir
    26. 

  26.       size: 23861319
    27. 

  27.       nfiles: 2
    28. 

  28.     - path: src/featurization.py
    29. 

  29.       md5: 02180903aa05599ceaa6ff6ee2471d00
    30. 

  30.       size: 2480
    31. 

  31.     params:
    32. 

  32.       params.yaml:
    33. 

  33.         featurize.max_features: 3000
    34. 

  34.         featurize.ngrams: 1
    35. 

  35.     outs:
    36. 

  36.     - path: data/features
    37. 

  37.       md5: 5a704a8a841240c85520c8d76e461791.dir
    38. 

  38.       size: 10805427
    39. 

  39.       nfiles: 2
    40. 

  40.   train:
    41. 

  41.     cmd: python src/train.py data/features model.pkl
    42. 

  42.     deps:
    43. 

  43.     - path: data/features
    44. 

  44.       md5: 5a704a8a841240c85520c8d76e461791.dir
    45. 

  45.       size: 10805427
    46. 

  46.       nfiles: 2
    47. 

  47.     - path: src/train.py
    48. 

  48.       md5: 3ffc5530112ca028ac61a3c8efeb0516
    49. 

  49.       size: 975
    50. 

  50.     params:
    51. 

  51.       params.yaml:
    52. 

  52.         train.min_split: 8
    53. 

  53.         train.n_est: 100
    54. 

  54.         train.seed: 20170428
    55. 

  55.     outs:
    56. 

  56.     - path: model.pkl
    57. 

  57.       md5: 38cd63ec33442608804bbfbe2932820f
    58. 

  58.       size: 4199048
    59. 

  59.   evaluate:
    60. 

  60.     cmd: python src/evaluate.py model.pkl data/features scores.json prc.json roc.json
    61. 

  61.     deps:
    62. 

  62.     - path: data/features
    63. 

  63.       md5: 5a704a8a841240c85520c8d76e461791.dir
    64. 

  64.       size: 10805427
    65. 

  65.       nfiles: 2
    66. 

  66.     - path: model.pkl
    67. 

  67.       md5: 38cd63ec33442608804bbfbe2932820f
    68. 

  68.       size: 4199048
    69. 

  69.     - path: src/evaluate.py
    70. 

  70.       md5: 16a56ad9df4476e6d3b76a64fe46dbcc
    71. 

  71.       size: 1483
    72. 

  72.     outs:
    73. 

  73.     - path: prc.json
    74. 

  74.       md5: 6498cde2014d7a525a185ec0b33dd209
    75. 

  75.       size: 200787
    76. 

  76.     - path: roc.json
    77. 

  77.       md5: df83831c5824ea06fa7cd1918df2962f
    78. 

  78.       size: 70882
    79. 

  79.     - path: scores.json
    80. 

  80.       md5: 039eca5d7b4289de31db00695904d68d
    81. 

  81.       size: 73
    82.
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Integrate Google Cloud Storage
Use Google Storage
Select bucket
Upload key
Finish

Use Google Cloud Storage!

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

Specify your Google Storage bucket

Service Account Key

Congratulations!

example-get-started is now integrated with Google Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
Integrate AWS S3
Use S3 remote
Select bucket
Access key
Finish

Use AWS S3 as storage!

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

Specify your S3 bucket

Access key (If needed)

Congratulations!

example-get-started is now integrated with AWS S3!

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

Access key (If needed)

Congratulations!

example-get-started is now integrated with your S3 compatible storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes
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!

example-get-started is now integrated with Azure Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes