This project explains how to move from a Jupyter notebook phase to a production ready training script that can run in a distributed training mode using Azure ML, Horovod and TF
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Updated
May 16, 2021 - Jupyter Notebook
This project explains how to move from a Jupyter notebook phase to a production ready training script that can run in a distributed training mode using Azure ML, Horovod and TF
Making the official ludwigai/ludwig-ray-gpu image available for jupyterhub.
How to use Docker and Singularity containers in conjunction with TensorFlow and Horovod to do distributed training and upscale an AI app.
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