Prediction Model Deployment Task
(Redirected from Model deployment)
Jump to navigation
Jump to search
A Prediction Model Deployment Task is an ML model deployment task that involves a prediction model.
- Example(s):
- …
- Counter-Example(s):
- See: Machine Learning Model Deployment System, Machine Learning Model Deployment Task, Predictive Function Deployment Task.
References
2018
- (Wei & Cai, 2019) ⇒ Kewei Wei, and Guanjun Cai (2018) "Bring Intelligence to Where Critical Transactions Run–An Update from Machine Learning for z/OS". Released: June 7, 2018 08:12 AM, Updated: June 7, 2018 08:12 AM
- QUOTE: To support such a broadscale collaboration, your machine learning platform must have a well-defined machine learning workflow, from data ingestion and model training to model deployment, as shown below.
- QUOTE: To support such a broadscale collaboration, your machine learning platform must have a well-defined machine learning workflow, from data ingestion and model training to model deployment, as shown below.
2017
- (Meehan et al., 2017) ⇒ John Meehan, Cansu Aslantas, Stan Zdonik, Nesime Tatbul, and Jiang Du. (2017). “Data Ingestion for the Connected World.” In: CIDR.
1998
- (Kohavi & Provost, 1998) ⇒ Ron Kohavi, and Foster Provost. (1998). “Glossary of Terms.” In: Machine Leanring 30(2-3).
- QUOTE: Model deployment: The use of a learned model. Model deployment usually denotes applying the model to real data.