Objective of this challenge is to build a regression model using the input features to predict the target variable. You can use the input variables at time “T” to estimate the target at time “T”. Please note that it is not a forecasting problem. Please don't use the target variable at time T-1 and below for estimating the target variable at time "T". The data set as in the real world, will need some analysis and cleaning. The data provided has input variables in addition to time stamp. Some inputs may not be relevant. The target variable is the last column and called as “target_temp”. It is temperature of a bearing in a wind turbine. The data is provided for 2017 and 2018. Use 2017 data for training and 2018 data for testing (What do you think is the reason that we are not using random training and test as would normally be done) The steps that you followed in order to build the model are important than the end result. You can any machine learning model that you prefer. The goal is to get mean error less than 1.5 degrees. However, as stated above, the end result is less important than how you go about building the model.