Automobile price prediction
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.
