Ludwig - Image recognition model - MNIST
1.0

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

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

gtn star logo followed by the word workflows

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.
  • File
mnist_dataset.csv #main/mnist_dataset.csv mnist_dataset.csv file is created and contains three columns: image_path, label, and, split.
  • File
mnist_images.zip #main/mnist_images.zip PNG files containing the handwritten numbers
  • File

Steps

ID Name Description
3 Ludwig Experiment https://toolshed.g2.bx.psu.edu/view/paulo_lyra_jr/ludwig_applications/3e565bbe8b71

Outputs

ID Name Description Type
_anonymous_output_1 #main/_anonymous_output_1 n/a
  • File
_anonymous_output_2 #main/_anonymous_output_2 n/a
  • File
_anonymous_output_3 #main/_anonymous_output_3 n/a
  • File

Version History

1.0 (earliest) Created 28th Oct 2024 at 13:08 by Helena Rasche

Added/updated 4 files


Open master 89e5fc9
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Views: 167   Downloads: 60

Created: 28th Oct 2024 at 13:08

Last updated: 28th Oct 2024 at 13:08

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