Ludwig - Image recognition model - MNIST
2.0

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 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
  • File
_anonymous_output_2 #main/_anonymous_output_2 n/a
  • File
_anonymous_output_3 #main/_anonymous_output_3 n/a
  • File

Version History

2.0 (earliest) Created 2nd Jun 2025 at 11:01 by GTN Bot

Added/updated 4 files


Open master 8db1c12
help Creators and Submitter
Creators
Not specified
Submitter
Discussion Channel
Activity

Views: 49   Downloads: 7   Runs: 0

Created: 2nd Jun 2025 at 11:01

help Attributions

None

Total size: 34.1 KB
Powered by
(v.1.17.0-main)
Copyright © 2008 - 2025 The University of Manchester and HITS gGmbH