Workflow Type: Galaxy
Deep Learning image classifier model
Associated Tutorial
This workflows is part of the tutorial Train and Test a Deep learning image classifier with Galaxy-Ludwig, available in the GTN
Features
- Includes Galaxy Workflow Tests
Thanks to...
Workflow Author(s): Paulo Cilas Morais Lyra Junior, Junhao Qiu, Jeremy Goecks
Tutorial Author(s): Paulo Cilas Morais Lyra Junior, Junhao Qiu, Jeremy Goecks
Inputs
ID | Name | Description | Type |
---|---|---|---|
config.yaml | #main/config.yaml | The config.yaml file is crucial as it defines the entire structure of your machine learning experiment. This configuration file tells Ludwig how to process your data, what model to use, how to train it, and what outputs to generate. |
|
mnist_dataset.csv | #main/mnist_dataset.csv | mnist_dataset.csv file is created and contains three columns: image_path, label, and, split. |
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mnist_images.zip | #main/mnist_images.zip | PNG files containing the handwritten numbers |
|
Steps
ID | Name | Description |
---|---|---|
3 | Ludwig Experiment | toolshed.g2.bx.psu.edu/repos/paulo_lyra_jr/ludwig_applications/ludwig_experiment/2024.0.10.3 |
Outputs
ID | Name | Description | Type |
---|---|---|---|
_anonymous_output_1 | #main/_anonymous_output_1 | n/a |
|
_anonymous_output_2 | #main/_anonymous_output_2 | n/a |
|
_anonymous_output_3 | #main/_anonymous_output_3 | n/a |
|
Version History

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Views: 41 Downloads: 4 Runs: 0
Created: 2nd Jun 2025 at 11:01


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