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basic example of how to use uber's deep learning tool ludwig.

Prerequisites

• Python3
• VSCode/ Pycharm as development (IDE)
• Linux machine (Preferred)

Reference:

to install ludwig follow this video tutorial link

NB: The model that is used in this tutorial may not work and you may find this error:

ludwig train: error: one of the arguments -md/--model definition -mdef/--model definition file is required

This link is good and has brief description which is worth reading.

NB:

• The model is added already inside the project.
• Make sure you have Python3 installed on your machine.
• Install ludwig on your machine.

we can train a deep learning model using the following command:

ludwig experiment \
  --data_csv reuters-allcats.csv \
  --model_definition_file model_definition.yaml

After training we can evaluate the predictions of the model using the following command:

  ludwig predict \
  --data_csv reuters-allcats.csv \
  --model_path results/experiment_run_5/model/

Visualization

    ludwig visualize \
    --visualization learning_curves \
    --training_statistics results/experiment_run_5/training_statistics.json