One Hot Encoding | Handling Categorical Data | Day 27 | 100 Days of Machine Learning

One Hot Encoding is a method to convert categorical data into a binary matrix, addressing the challenges posed by categorical variables in machine learning models. Code used: https://github.com/campusx-official/100-days-of-machine-learning/tree/main/day27-one-hot-encoding ============================ 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 Instagram: https://www.instagram.com/campusx.official E-mail us at support@campusx.in ⌚Time Stamps⌚ 00:00 - Intro 00:28 - Revision 02:39 - One Hot Encoding 05:40 - Dummy Variable Trap 10:10 - OHE using most frequent variables 12:15 - Code Example 18:30 - Code Example using SKlearn