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The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.
Designed a robotic system using inference. Created a project idea, collected data set for classification, and justified network design choices based on technical analysis of accuracy and speed on the target system.