Project #6: Processing data from a visual IoT sensor of Fluid/Structure interactions with Machine Learning REU Students: Alexis Downing and Pete Orkweha Graduate mentor(s):Safa Bacanli and Sharare Zehtabian Faculty mentor(s): Andrew Dickerson and Damla Turgut Week #3 (June 17 – June 21, 2019) Accomplishments: Started literature review Experimentation of support vector regression, polynomial, random forest regression, and multi-layer perceptions algorithms Use of regression trees to figure out if the data was linear or not. I tried this on fiber B3’s dataset. Problem & Solutions Not knowing the “shape” of our data is Optimization cannot be further applied to the rand forest regressor. It still had significant percentage of errors. Plans for next week: Investigate the weight used by our multi-layer perceptrons Used the investigated weight to find how “flat” or small the value of the loss function The learning rate should be increased or decreased by the value of the loss function