#kubeflow
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Accelerating ETL on KubeFlow with RAPIDS

Aug 30, 2022 11 minute read #dask, #etl, #kubeflow, #pandas, #rapids, #technical-walkthrough Archive

In the machine learning and MLOps world, GPUs are widely used to speed up model training and inference, but what about the other stages of the workflow like ETL pipelines or hyperparameter optimization?
Using Dask on KubeFlow with the Dask Kubernetes Operator

Jul 27, 2022 10 minute read #python, #dask, #kubernetes, #kubeflow, #operator, #data-science

Kubeflow is a popular Machine Learning and MLOps platform built on Kubernetes for designing and running Machine Learning pipelines for training models and providing inference services. It has a notebook service that lets you launch interactive Jupyter servers (and more) on your Kubernetes cluster as well as a pipeline service with a DSL library written in Python for designing and building repeatable workflows. It also has tools for hyperparameter tuning and running model inference servers, everything you need to build a robust ML service.
Running Kubeflow inside Kind with GPU support

Jan 27, 2022 8 minute read #community, #open-source, #kubernetes, #kind, #kubeflow, #gpus

This week I’ve been playing around with Kubeflow as part of a larger effort to make it simpler to use Dask and RAPIDS in MLOps workflows.

Accelerating ETL on KubeFlow with RAPIDS