Predicts the price of a car based on different variables such as make and technical specifications.
Workflow of this experiment 1. Creating a model has three steps such as, * Get the data * Prepare the data - Have to pre-processing the datas 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 prices. 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.