ThoughtWorks Guide to Evaluating MLOps Platforms
The MLOps scene is exploding. New tools enter the scene every week, leaving leaders with a long list of vendors to consider. It’s what analyst house Gartner calls a “glut of innovation”. The rapid expansion of MLOps platforms is only one part of the overall AI landscape.
This guide from Thoughtworks helps you cut through the noise. You will learn:
- How to identify where platforms fit in the ML lifecycle
- Whether non-machine learning tools fit in the MLOps stack
- The difference between ML tools and ML platforms
- How Techniques for planning integrations and automations
- Common pitfalls to avoid when buying ML tols
- How to structure your evaluation
This guide also includes an overview of the future of MLOps, and profiles the platforms and tools used by machine learning leaders today.