The Auto MPG dataset is a well-known dataset from the UCI Machine Learning Repository. It contains information about cars and is commonly used for regression tasks, particularly for predicting the miles per gallon (MPG) of cars based on other features.

Key Features of the Auto MPG Dataset:

• mpg: Miles per gallon (the target variable for regression tasks).
• cylinders: Number of cylinders in the engine.
• displacement: Engine displacement (in cubic inches).
• horsepower: Engine horsepower.
• weight: Weight of the car (in pounds).
• acceleration: Time to accelerate from 0 to 60 mph (in seconds).
• model year: Year of manufacture (e.g., 70 for 1970).
• origin: Country of origin (1 = USA, 2 = Europe, 3 = Japan).
• car name: String identifier for the car model.

Additional Notes:

1. The dataset contains 398 entries.
2. There are missing values in the horsepower column, which are often represented as ?.
3. It’s widely used for exploring relationships between automobile characteristics and fuel efficiency.

You can get the dataset here