Title: Applying ML/AI To Data Management Lifecycle Functions
Project ID: lKQiB16
Domain(s): Data Science
Description:
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.
Additionally, refocus human efforts towards tuning parameters vs. data entry of metadata.
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.
Additionally, refocus human efforts towards tuning parameters vs. data entry of metadata
Desired Skills:
Systems Engineering, Data Engineering, Data Analytics, NLP, AI/ML
Clearance-
US Citizenship Required: No
Active Clearance or Background Investigation Required: No
Level Needed:
Team Information-
Targeted Students: Grad
Team Size: 5 or More
Details:
Specific Requirements-
Focus on Particular University: Yes
Details: George Mason University, Data Analytics Engineering Capstone
Timeline-
Focus Timeline: No
Details:
Funding-
Potential Funding:No
Note: Availability of funds not guaranteed
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