This projects aims to use a common but effective method, clustering analysis to categorize the type of vehicles that are included in the data set. Two clustering method are employed in this project; Hierarchical and K-means.

The projects aims to use machine learning techniques to forecasts the number of dengue cases in Iquitos, Peru and San Juan, Puerto Rico, using data provided by the center of diseases and control in the U.S.

A large wine manufacturer is studying the data in order to predict the number of wine cases ordered based upon the wine characteristics. If the wine manufacturer can predict the number of cases, then that manufacturer will be able to adjust their wine offering to maximize sales. the objective is to build a count regression model to predict the number of cases of wine that will be sold given certain properties of the wine