Green Seattle - Prediction and Visualization

Green Seattle is an inter-disciplinary project in Clearn Energy Insitute (CEI) collaborated by seven students majoring in Chemical Sciences, Political Science and Electrical Engineering. The first part of Green Seattle is focused on predicting Seattle Traffic Trends (codes are publicly available here), while the second is focused on Visualizing Seattle Traffic Trends, as well as outputs of a regression model seeking to predict future traffic patterns based on user inputs (codes are publicly available here). I am responsible for implementing machine learning framework for predicting Traffic Trends using Tensorflow 2.0, and visualizing the model in TensorBoard.