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arcticbear
/
example-get-started
mirror of https://github.com/iterative/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.       hash: md5
    8. 

  8.       md5: 22a1a2931c8370d3aeedd7183606fd7f
    9. 

  9.       size: 14445097
    10. 

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

  11.       hash: md5
    12. 

  12.       md5: f54d670ac8a4f63206781fc31d1f2651
    13. 

  13.       size: 2231
    14. 

  14.     params:
    15. 

  15.       params.yaml:
    16. 

  16.         prepare.seed: 20170428
    17. 

  17.         prepare.split: 0.2
    18. 

  18.     outs:
    19. 

  19.     - path: data/prepared
    20. 

  20.       hash: md5
    21. 

  21.       md5: 153aad06d376b6595932470e459ef42a.dir
    22. 

  22.       size: 8437363
    23. 

  23.       nfiles: 2
    24. 

  24.   featurize:
    25. 

  25.     cmd: python src/featurization.py data/prepared data/features
    26. 

  26.     deps:
    27. 

  27.     - path: data/prepared
    28. 

  28.       hash: md5
    29. 

  29.       md5: 153aad06d376b6595932470e459ef42a.dir
    30. 

  30.       size: 8437363
    31. 

  31.       nfiles: 2
    32. 

  32.     - path: src/featurization.py
    33. 

  33.       hash: md5
    34. 

  34.       md5: e22789fc9581cad11ef7a6fa3aa3f17b
    35. 

  35.       size: 4158
    36. 

  36.     params:
    37. 

  37.       params.yaml:
    38. 

  38.         featurize.max_features: 100
    39. 

  39.         featurize.ngrams: 1
    40. 

  40.     outs:
    41. 

  41.     - path: data/features
    42. 

  42.       hash: md5
    43. 

  43.       md5: 2bf57a6e0f302c86452aa907584e1397.dir
    44. 

  44.       size: 1556290
    45. 

  45.       nfiles: 2
    46. 

  46.   train:
    47. 

  47.     cmd: python src/train.py data/features model.pkl
    48. 

  48.     deps:
    49. 

  49.     - path: data/features
    50. 

  50.       hash: md5
    51. 

  51.       md5: 2bf57a6e0f302c86452aa907584e1397.dir
    52. 

  52.       size: 1556290
    53. 

  53.       nfiles: 2
    54. 

  54.     - path: src/train.py
    55. 

  55.       hash: md5
    56. 

  56.       md5: 324001573ed724e5ae092226fcf9ca30
    57. 

  57.       size: 1666
    58. 

  58.     params:
    59. 

  59.       params.yaml:
    60. 

  60.         train.min_split: 0.01
    61. 

  61.         train.n_est: 50
    62. 

  62.         train.seed: 20170428
    63. 

  63.     outs:
    64. 

  64.     - path: model.pkl
    65. 

  65.       hash: md5
    66. 

  66.       md5: b0c341636502e7f8fcddb733b6d23dd0
    67. 

  67.       size: 1854891
    68.
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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