Intro_To_CNN_v1.0.11.0

statistics-CNN/intro-to-cnn-v1-0-11-0

Author(s)
Kaivan Kamali
version Version
1
last_modification Last updated
Dec 11, 2023
license License
CC-BY-4.0
galaxy-tags Tags

Features

Tutorial
hands_on Deep Learning (Part 3) - Convolutional neural networks (CNN)

Workflow Testing
Tests: ✅
Results: Not yet automated
FAIRness purl PURL
https://gxy.io/GTN:W00214
RO-Crate logo with flask Download Workflow RO-Crate Workflowhub cloud with gears logo View on (Dev) WorkflowHub
Launch in Tutorial Mode question
galaxy-download Download
flowchart TD
  0["ℹ️ Input Dataset\nX_test"];
  style 0 stroke:#2c3143,stroke-width:4px;
  1["ℹ️ Input Dataset\nX_train"];
  style 1 stroke:#2c3143,stroke-width:4px;
  2["ℹ️ Input Dataset\ny_test"];
  style 2 stroke:#2c3143,stroke-width:4px;
  3["ℹ️ Input Dataset\ny_train"];
  style 3 stroke:#2c3143,stroke-width:4px;
  4["Create a deep learning model architecture"];
  5["To categorical"];
  3 -->|output| 5;
  6["Create deep learning model"];
  4 -->|outfile| 6;
  7["Deep learning training and evaluation"];
  6 -->|outfile| 7;
  1 -->|output| 7;
  5 -->|outfile| 7;
  8["Model Prediction"];
  7 -->|outfile_object| 8;
  0 -->|output| 8;
  9["Machine Learning Visualization Extension"];
  8 -->|outfile_predict| 9;
  2 -->|output| 9;

Inputs

Input Label
Input dataset X_test
Input dataset X_train
Input dataset y_test
Input dataset y_train

Outputs

From Output Label

Tools

Tool Links
toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_builder/keras_model_builder/1.0.10.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/bgruening/keras_model_config/keras_model_config/1.0.10.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/bgruening/keras_train_and_eval/keras_train_and_eval/1.0.11.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/bgruening/ml_visualization_ex/ml_visualization_ex/1.0.11.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/bgruening/model_prediction/model_prediction/1.0.11.0 View in ToolShed
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_to_categorical/sklearn_to_categorical/1.0.10.0 View in ToolShed

To use these workflows in Galaxy you can either click the links to download the workflows, or you can right-click and copy the link to the workflow which can be used in the Galaxy form to import workflows.

Importing into Galaxy

Below are the instructions for importing these workflows directly into your Galaxy server of choice to start using them!
Hands-on: Importing a workflow
  • Click on Workflow on the top menu bar of Galaxy. You will see a list of all your workflows.
  • Click on galaxy-upload Import at the top-right of the screen
  • Provide your workflow
    • Option 1: Paste the URL of the workflow into the box labelled “Archived Workflow URL”
    • Option 2: Upload the workflow file in the box labelled “Archived Workflow File”
  • Click the Import workflow button

Below is a short video demonstrating how to import a workflow from GitHub using this procedure:

Video: Importing a workflow from URL

Version History

Version Commit Time Comments
2 ce48b25d3 2023-11-08 18:57:37 Fixed lint issues
1 0c206197d 2023-11-08 16:45:26 Renamed workflow and test yml file

For Admins

Installing the workflow tools

wget https://training.galaxyproject.org/training-material/topics/statistics/tutorials/CNN/workflows/Intro_To_CNN_v1_0_11_0.ga -O workflow.ga
workflow-to-tools -w workflow.ga -o tools.yaml
shed-tools install -g GALAXY -a API_KEY -t tools.yaml
workflow-install -g GALAXY -a API_KEY -w workflow.ga --publish-workflows