The project is to analyze the data from Capital Bikeshare system in Washington D.C. using given data.
a) Use exploratory data analysis (EDA) to explore the average usage of the system by day of the week and month of the year.
b) Build linear model to predict the cnt variable.
d) Build a random forest model for both classification and regression. Compare the out-of-sample performance with LASSO models. Discuss advantages and disadvantages of tree-based models vs generalized linear models.
I will provide with all the data and files upon confirming that you’re the right candidate for this project.
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