predicts the price of a car based on different variables such as make and technical specifications.
1. Creating a model has three steps such as, get the data prepare the date - have to pre-process the dates before analyzing. missing values need to be cleaned so the model can analyze the data correctly. define features - build a model that uses a subset of the features in our dataset. 2. Train the model - choose and apply an algorithm to test the model to see how closely it's able to predict. 3. score and test the model - predict new automobile prices. The output shows the predicted values for price and the known values from the test data.