-> The main objective of the project is to predict the future sale price of a bulldozer, given its characteristics and previous examples of how much similar bulldozers have been sold for.
-> The data used is time series dataset downloaded from the Kaggle Bluebook for Bulldozers competition.
-> Data wrangling concepts like data cleaning (outlier detection and Imputation) and data enriching is done.
-> OneHotEncoding is used to turn categorical values into numbers.
-> The Random Forest Regressor model is used.
-> The model is evaluated by using RMSLE (Root Mean Square Log Error) as evaluation metric