Move over Kubeflow, there's a new sheriff in town: Github Actions 🤠
June 20, 2022 - Michael Schuster - 15 mins read
This tutorial presents an easy and quick way to use GitHub Actions to run ML pipelines in the cloud. We showcase this functionality using Microsoft's Azure Cloud but you can use any cloud provider you like.
Podcast: ML Engineering with Ben Wilson
June 8, 2022 - Alex Strick van Linschoten - 1 min read
This week I spoke with Ben Wilson, author of 'Machine Learning Engineering in Action', a jam-backed guide to all the lessons that Ben has learned over his years working to help companies get models out into the world and run them in production.
The Framework Way is the Best Way: the pitfalls of MLOps and how to avoid them
May 24, 2022 - Stefan Nica - 9 mins read
As our AI/ML projects evolve and mature, our processes and tooling also need to keep up with the growing demand for automation, quality and performance. But how can we possibly reconcile our need for flexibility with the overwhelming complexity of a continuously evolving ecosystem of tools and technologies? MLOps frameworks promise to deliver the ideal balance between flexibility, usability and maintainability, but not all MLOps frameworks are created equal. In this post, I take a critical look at what makes an MLOps framework worth using and what you should expect from one.
What's New in v0.8.0: Extend ZenML Any Way You Like!
May 18, 2022 - Alex Strick van Linschoten - 5 mins read
Release notes for the new version of ZenML. We've added a ton of extensibility improvements, documentation and guides that take away most of the hard work of figuring out how to add custom components. Our CLI also has been beautified and it should even run a bit faster too!
All Continuous, All The Time: Pipeline Deployment Patterns with ZenML
May 11, 2022 - Safoine El Khabich - 12 mins read
Connecting model training pipelines to deploying models in production is seen as a difficult milestone on the way to achieving MLOps maturity for an organization. ZenML rises to the challenge and introduces a novel approach to continuous model deployment that renders a smooth transition from experimentation to production.
What's New in v0.7.2 and v0.7.3: HuggingFace, Weights & Biases, LightGBM, XGBoost, and more!
April 28, 2022 - Hamza Tahir - 5 mins read
The release adds experiment tracking stack components, integrations with HuggingFace, Weights & Biases and also improvements to how the Seldon Core deployer handles secrets from the secrets manager component.