How to turn a Jupyter Notebook into a deployable artifact
From Jupyter Notebook to production-ready artifact: explore our guide to using KitOps and ModelKit for seamless deployment.
Jesse Williams COO/CMO · July 8, 2024
The Jozu Blog
Accelerating into AI: Lessons from AWS
Learn why competitive advantages in the post-AI world will come from creating an internal AI team, and how to sequence their projects for impact and safety.
Brad Micklea · June 11, 2024
10 Best Open-Source MLOps Pipeline Tools (2026) | Free & Proven
Build a production-ready MLOps pipeline with these 10 free, open-source tools — from experiment tracking to model deployment and monitoring.
Jesse Williams COO/CMO · June 6, 2024
How to Build an MLOps Pipeline: Step-by-Step Guide (2026)
Build your first MLOps pipeline from scratch — data ingestion, model training, CI/CD, deployment, and monitoring. Includes tool recommendations and code examples.
Jesse Williams COO/CMO · June 4, 2024
When to Dockerize vs. When to use ModelKit
ML development can often be a cumbersome and iterative process, with many open source tools, built to handle specific parts of the machine learning workflow. In this post we explore when to use Docker and when to use ModelKits.
Jesse Williams COO/CMO · May 30, 2024
KitOps: The Bridge Between AI/ML Models and DevOps
Discussing the current state of the KitOps project, where the project is headed, and some of our early ideas for productizing and releasing Jozu.
Jesse Williams COO/CMO · May 17, 2024