Develop a machine learning algorithm to edit seafloor bathymetry soundings.
Type of Data:
Time series of depth soundings collected by a sonar on a ship (e.g., time, longitude, latitude, depth, . . .)
Approximate Data Size:
440 million records from more than 8000 month-long ship cruises
Domain Expert:
Methods Expert:
Methods Student Openings:
1.00
Methods Student Funding:
no
Methods Student Prerequisites:
* python and jupyter notebooks.
* a course in Probability and statistics
* Familiarity with boosting
* Google maps API: https://developers.google.com/maps/