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This document summarizes a student project to predict the number of bike-sharing users in Washington D.C. using machine learning models. The students will use a public dataset containing hourly bike rental data along with weather and seasonal information from 2011-2012. They will explore the data using plots to understand relationships between bike usage and factors like temperature, humidity and time of day. Different machine learning models like RNNs will be tested and hyperparameters like batch size, epo

Author

Battagiri Sai Jyothi

Language

EN