From dfae704ade04983d9d84e5853eba7e8de86b47c2 Mon Sep 17 00:00:00 2001 From: Gibson Chikafa Date: Tue, 4 Feb 2025 13:17:21 +0100 Subject: [PATCH] [HWORKS-1990] Add ray related images to the general env info doc page (#441) --- docs/user_guides/projects/python/python_env_overview.md | 7 ++++++- 1 file changed, 6 insertions(+), 1 deletion(-) diff --git a/docs/user_guides/projects/python/python_env_overview.md b/docs/user_guides/projects/python/python_env_overview.md index 97c884ebb..1f337a91e 100644 --- a/docs/user_guides/projects/python/python_env_overview.md +++ b/docs/user_guides/projects/python/python_env_overview.md @@ -35,11 +35,16 @@ The `FEATURE ENGINEERING` environments can be used in [Jupyter notebooks](../jup ### Model training -The `MODEL TRAINING` environments can be used in [Jupyter notebooks](../jupyter/python_notebook.md) or a [Python job](../jobs/python_job.md). +The `MODEL TRAINING` environments can be used in [Jupyter notebooks](../jupyter/python_notebook.md) or a [Python job](../jobs/python_job.md) or in a [Ray job](../jobs/ray_job.md). * `tensorflow-training-pipeline` to train TensorFlow models * `torch-training-pipeline` to train PyTorch models * `pandas-training-pipeline` to train XGBoost, Catboost and Sklearn models +* `ray_training_pipeline` a general purpose environment for distributed training using Ray framework to train + XGBoost and Sklearn models. Should be used in [Ray job](../jobs/ray_job.md). It can be customized to install + additional dependencies of your choice. +* `ray_torch_training_pipeline` for distributed training of PyTorch models using Ray framework in a [Ray job](../jobs/ray_job.md) +* `ray_tensorflow_training_pipeline` for distributed training of TensorFlow models using Ray framework in a [Ray job](../jobs/ray_job.md) ### Model inference