Using the Git workflow in Amazon SageMaker Pipelines

Amazon SageMaker Pipelines is a new capability of Amazon SageMaker that makes it easy for data scientists and engineers to build, automate, and scale end to end machine learning pipelines.

In this video, I show you how to train and deploy automatically different versions of your machine learning models using Amazon SageMaker Studio, Amazon SageMaker Pipelines, and a familiar Git workflow. This is a followup to https://youtu.be/Hvz2GGU3Z8g, so you may want to watch that one first.

About the Author

Julien Simon is the Chief Evangelist at Arcee AI , specializing in Small Language Models and enterprise AI solutions. Recognized as the #1 AI Evangelist globally by AI Magazine in 2021, he brings over 30 years of technology leadership experience to his role.

With 650+ speaking engagements worldwide and 350+ technical blog posts, Julien is a leading voice in practical AI implementation, cost-effective AI solutions, and the democratization of artificial intelligence. His expertise spans open-source AI, Small Language Models, enterprise AI strategy, and edge computing optimization.

Previously serving as Principal Evangelist at AWS and Chief Evangelist at Hugging Face, Julien has authored books on Amazon SageMaker and contributed to the open-source AI ecosystem. His mission is to make AI accessible, understandable, and controllable for everyone.