Speaker "Antje Barth" Details Back



Building End-to-End Machine Learning Workflows with Kubernetes, Kubeflow Pipelines, and BERT


Kubeflow is a popular open-source machine learning (ML) toolkit for Kubernetes users who want to build custom ML pipelines. Kubeflow Pipelines is an add-on to Kubeflow that lets you build and deploy portable and scalable end-to-end ML workflows. In this session, I show you how to get started with Kubeflow Pipelines on AWS. I also demonstrate how you can integrate powerful Amazon SageMaker features such as data labeling, large-scale hyperparameter tuning, distributed training jobs, secure and scalable model deployment using Amazon SageMaker Components for Kubeflow Pipelines.
Who is this presentation for?
Machine Learning Engineers, Data Scientists, Data Engineers


Antje is a Developer Advocate for AI and Machine Learning at Amazon Web Services (AWS) based in Düsseldorf, Germany. She is co-author of the O'Reilly Book, "Data Science on AWS." Antje is also co-founder of the Düsseldorf chapter of Women in Big Data. Antje frequently speaks at AI and Machine Learning conferences and meetups around the world. Besides ML/AI, Antje is passionate about helping developers leverage Big Data, container and Kubernetes platforms in the context of AI and Machine Learning. Previously, Antje worked in technical evangelism and solutions engineering at MapR and Cisco.