Bikeshare in Language R

 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.

c) Classification 

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. 

Thank you