Overview
According to a 2019 report, 85% of AI projects fail to deliver on their intended promises to business. Why do so many projects fail?
Overview - ML Projects
- ML is still research, therefore it is very challenging to aim for 100% success rate.
- Many ML projects are technically infeasible or poorly scoped.
- Many ML projects never make the leap into production.
- Many ML projects have unclear success criteria.
- Many ML projects are poorly managed.
Last modified 2yr ago