In this workshop, we build real-world AI and machine learning pipelines using Kubeflow, TensorFlow, TensorFlow Extended (TFX), Keras, PyTorch, and Amazon SageMaker. 

Described in the 2017 paper, TFX is used internally by thousands of Google data scientists and engineers across every major product line within Google.

Kubeflow is a modern, end-to-end pipeline orchestration framework that embraces the latest AI best practices including hyper-parameter tuning, distributed model training, and model tracking.

We will deploy everything on AWS including Amazon SageMaker, Elastic Kubernetes Service (EKS), and Managed Workflows for Airflow.

 

Pre-requisites

Modern browser - and that's it!

Every attendee will receive a cloud instance

Nothing will be installed on your local laptop

Everything can be downloaded at the end of the workshop

Chris Fregly is a Developer Advocate for AI and Machine Learning at Amazon Web Services (AWS) based in San Francisco, California. He is co-author of the O'Reilly Book, "Data Science on AWS."

 

Chris is also the Founder of many global meetups focused on Apache Spark, TensorFlow, and KubeFlow. He regularly speaks at AI and Machine Learning conferences across the world including O’Reilly AI & Strata, Open Data Science Conference (ODSC), and GPU Technology Conference (GTC).

 

Previously, Chris was Founder at PipelineAI where he worked with many AI-first startups and enterprises to continuously deploy ML/AI Pipelines using Apache Spark ML, Kubernetes, TensorFlow, Kubeflow, Amazon EKS, and Amazon SageMaker.