Conclusion. Encoding categorical data is a crucial step in data preprocessing. By converting categorical data into a numeric format, machine learning models can interpret and work more effectively.

The Data Science Lab. Data Prep for Machine Learning: Encoding. Dr. James McCaffrey of Microsoft Research uses a full code program and screenshots to explain how to programmatically encode categorical ...

For example, the one-hot encoding with Moore FSM type is preferable for the high-speed designs, while Gray encoding being preferable for the low-power applications, etc. ... It is advisable to develop ...