Title: Applying ML\/AI To Data Management Lifecycle Functions
\nProject ID: lKQiB16
\nDomain(s): Data Science<\/p>\n
Description:<\/p>\n
Potential goals to consider: Streamline data tagging to increase turnaround time for discovery, orchestrate metadata between search technology tools, data management tools, and other prevalent technologies, and determine typical uses of data.
\nAdditionally, refocus human efforts towards tuning parameters vs. data entry of metadata.<\/p>\n
Potential goals to consider: Streamline data tagging to increase turnaround time for discovery, orchestrate metadata between search technology tools, data management tools, and other prevalent technologies, and determine typical uses of data.
\nAdditionally, refocus human efforts towards tuning parameters vs. data entry of metadata<\/p>\n
Desired Skills:
\nSystems Engineering, Data Engineering, Data Analytics, NLP, AI\/ML<\/p>\n
US Citizenship Required: No
\nActive Clearance or Background Investigation Required: No
\nLevel Needed: <\/p>\n
Targeted Students: Grad
\nTeam Size: 5 or More
\nDetails: <\/p>\n
Focus on Particular University: Yes
\nDetails: George Mason University, Data Analytics Engineering Capstone<\/p>\n
Focus Timeline: No
\nDetails: <\/p>\n
Potential Funding:No
\nNote: Availability of funds not guaranteed<\/p>\n