Technology readiness levels for machine learning systems
The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. En...
| Principais autores: | , , , , , , , , , , , , , , |
|---|---|
| Formato: | Journal article |
| Idioma: | English |
| Publicado em: |
Springer Nature
2022
|