Register
Login
Resources
Docs Blog Datasets Glossary Case Studies Tutorials & Webinars
Product
Data Engine LLMs Platform Enterprise
Pricing Explore
Connect to our Discord channel
Resources  
Docs Blog Datasets Glossary Case Studies Tutorials & Webinars
Explore Pricing
Product  
Data Engine LLMs Platform Enterprise
Connect to Dagshub Discord channel
Register
Login

avatar kingabzpro
/
dvc-getting-started

Watch 1
Issues 0 Pull Requests 0 Discussions 0 Invite collaborators

dvc.lock 2.3 KB
Permalink History Raw

You have to be logged in to leave a comment. Sign In
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87 
  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: 22a1a2931c8370d3aeedd7183606fd7f
    8. 

  8.       size: 14445097
    9. 

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

  10.       md5: f09ea0c15980b43010257ccb9f0055e2
    11. 

  11.       size: 1627
    12. 

  12.     params:
    13. 

  13.       params.yaml:
    14. 

  14.         prepare.seed: 25
    15. 

  15.         prepare.split: 0.3
    16. 

  16.     outs:
    17. 

  17.     - path: data/prepared
    18. 

  18.       md5: 0c3f6a5b112ba09a66d801c318c3c7dd.dir
    19. 

  19.       size: 8447363
    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: 0c3f6a5b112ba09a66d801c318c3c7dd.dir
    26. 

  26.       size: 8447363
    27. 

  27.       nfiles: 2
    28. 

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

  29.       md5: e0265fc22f056a4b86d85c3056bc2894
    30. 

  30.       size: 2570
    31. 

  31.     params:
    32. 

  32.       params.yaml:
    33. 

  33.         featurize.max_features: 200
    34. 

  34.         featurize.ngrams: 2
    35. 

  35.     outs:
    36. 

  36.     - path: data/features
    37. 

  37.       md5: fc7959e8adf6de8c1edeb8946923f1d1.dir
    38. 

  38.       size: 2226676
    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: fc7959e8adf6de8c1edeb8946923f1d1.dir
    45. 

  45.       size: 2226676
    46. 

  46.       nfiles: 2
    47. 

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

  48.       md5: c3961d777cfbd7727f9fde4851896006
    49. 

  49.       size: 1006
    50. 

  50.     params:
    51. 

  51.       params.yaml:
    52. 

  52.         train.min_split: 0.01
    53. 

  53.         train.n_est: 50
    54. 

  54.         train.seed: 20170428
    55. 

  55.     outs:
    56. 

  56.     - path: model.pkl
    57. 

  57.       md5: 67e822d741a6a25da0327799b3e5b3a1
    58. 

  58.       size: 1607568
    59. 

  59.   evaluate:
    60. 

  60.     cmd: python src/evaluate.py model.pkl data/features
    61. 

  61.     deps:
    62. 

  62.     - path: data/features
    63. 

  63.       md5: fc7959e8adf6de8c1edeb8946923f1d1.dir
    64. 

  64.       size: 2226676
    65. 

  65.       nfiles: 2
    66. 

  66.     - path: model.pkl
    67. 

  67.       md5: 67e822d741a6a25da0327799b3e5b3a1
    68. 

  68.       size: 1607568
    69. 

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

  70.       md5: 44e714021a65edf881b1716e791d7f59
    71. 

  71.       size: 2418
    72. 

  72.     outs:
    73. 

  73.     - path: evaluation.json
    74. 

  74.       md5: ead5c1f3b237b63f30e72f63917fd4f9
    75. 

  75.       size: 76
    76. 

  76.     - path: evaluation/importance.png
    77. 

  77.       md5: 4128e7aa5b1b2902188eadf360dc37b4
    78. 

  78.       size: 33050
    79. 

  79.     - path: evaluation/plots/confusion_matrix.json
    80. 

  80.       md5: 6ceae30306cc54a42f25c8359bf380dc
    81. 

  81.       size: 196433
    82. 

  82.     - path: evaluation/plots/precision_recall.json
    83. 

  83.       md5: b2e82d562a0100d7fbd211aa7c81d28c
    84. 

  84.       size: 156301
    85. 

  85.     - path: evaluation/plots/roc.json
    86. 

  86.       md5: f2253715c9ed358f048bec11e1899e24
    87. 

  87.       size: 72188
    88.
Prev
Next
Tip!

Press p or to see the previous file or, n or to see the next file

Comments

Write Preview
Loading...
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!

dvc-getting-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!

dvc-getting-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!

dvc-getting-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!

dvc-getting-started is now integrated with Azure Cloud Storage!

Delete Storage Key

Are you sure you want to delete this access key?

No
Yes