Distributed ML Ops
Use Cases and Deployment Scope
Distributed Machine Learning Operations is very important for delivering Machine Learning Projects to our customers.
Pros
- Helps us to take on more client projects
- Can be used by data analysts as well as casual users
Cons
- Out of the box support for major cloud vendors
Most Important Features
- Allowing distributed learning
- Easy to learn
Return on Investment
- We can handle 4 to 6 times more projects at the same time with our team
- We stay engaged with our customers well beyond the project duration
Other Software Used
Jira Software, GitLab
