Lead ML implementation with confidence
The ML Project Checklist aims at guiding you through the implementation of an ML system. It serves as your roadmap, listing in detail what you need to do and in which order. End-to-end ML projects are broken down into 9 phases of 4 tasks each.
The checklist comes as a 3-page PDF document. You’ll also get access to a mini-course.
Mini-course
In addition to the checklist to download, you'll get access to 3 lessons:
The 9 software components that need to be built when creating an ML system: architecture diagram + explanations
The investor’s approach to ML projects: principles behind CRISP—OWNML
How to use the checklist + explanations (video)
“This framework has become our guide. It has helped us expedite the entire process from use case idea to MVP deployment, beyond our expectations.”
About the methodology
The checklist follows a methodology called CRISP—OWNML (Cross-Industry Standard Process for building your own Machine Learning system) which minimizes the risks and costs of ML projects, and allows to make the most efficient use of your team's time. It can also be used by very small teams with limited ressources (all the way down to a team of 1).
The 9 phases are:
Ideate
Prepare Data
Evaluate
Build Model
Analyze
Shadow-Deploy
Update
Secure
Integrate
Get access
Download the detailed checklist and get access to all our courses for leaders & innovators with an OWNML+ subscription. No commitment — cancel anytime.