Applying data science methods and models to a business use case represents the ultimate goal of most data science work. But crossing the gap between data science theory and application is challenging, requiring the data scientist to understand a business domain, unique data associated with that domain, and the needs and requirements of a customer.
This article provides an approach to applying data science methods, such as machine learning, to a notional business use case. Follow this article to learn how to:
- Receive a Business Scenario and Data.
- Conduct Data Exploration.
- Apply a Machine Learning Classification Model.
- Make Predictions and Recommendations Based on the Model.
The Scenario:
You work for an automotive company as a data scientist. The company has a reputation for making sporty and quick cars, and is developing a new car for the 1983 model year. The design team has several new drivetrain configurations to choose from, each of which has implications for performance and fuel economy.