Catalog Entries |
|
|
 |
||
 | Select the Course Number to get further detail on the course. Select Schedule Type to find available sections of the course as well as section specific prerequisites. Prerequisites listed in the catalog descriptions are recommended and may not be the same as registration prerequisites in PipelineMT. Use the Look Up Classes link for a grid display of important course information as well as prerequisites and memo notes about the section. |
| DATA 6330 - Model Optimization and Deployment |
|
The optimization and deployment of machine learning models. Techniques for fine-tuning parameters for developing the best model for the presented business problems. Applications through internal and cloud infrastructures also used to identify optimal techniques for deployment of models to operationalize into production.
3.000 Credit hours Levels: Graduate Schedule Types: Combined Lecture/Lab Basic and Applied Sciences Department Course Attributes: College of Basic & Applied |
|