100 Days of Machine Learning | CampusX - Handling Mixed Variables | Feature Engineering

When dealing with mixed variables (both numerical and categorical) in feature engineering, strategies involve techniques like one-hot encoding for categorical variables and scaling for numerical ones. These methods ensure compatibility and enhance the effectiveness of mixed variable data in machine learning models. Code Used : https://github.com/campusx-official/100-days-of-machine-learning/tree/main/day33-handling-mixed-variables ============================ Do you want to learn from me? Check my affordable mentorship program at : https://learnwith.campusx.in/s/store ============================ 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official CampusX on Instagram for daily tips: https://www.instagram.com/campusx.official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Discord: https://discord.gg/PsWu8R87Z8 E-mail us at [email protected]