Automobile price prediction-IT17006880

Prepare the data - Cleaned the data by removing the normalized losses column since it has a large number of missing values Define Features - make, body-style, wheel-base, engine-size, horsepower, peak-rpm, highway-mpg, price Choose Algorithm - Split data(75% for training the model and 25% for testing) - The machine-learning category used was Linear Regression module under Regression category Predict new automobile prices - view the experiment from the score model