Your First Machine Learning Project - Crash Course - Feature Encoding in ML: Beyond the Basics

Welcome to the sixteenth video of the series "Build your First Machine Learning Project". This is video is all about the Feature Encoding in Machine Learning. Feature encoding is a process of converting categorical or non-numeric data into a numerical format that can be used as input for machine learning algorithms. Many machine learning algorithms require input data to be in numerical form, and feature encoding is a crucial step in preparing data for these algorithms to make accurate predictions or classifications. Let's understand it in deep. Chapters 0:00 Intro to feature encoding 1:25 Various Approaches 1:40 First approach 3:16 Second approach 5:08 Third approach 7:09 Fourth approach 7:49 Conclusion In order to make the best out of this, please watch this series in the order in playlist: Build Your First ML Model Playlist: https://www.youtube.com/watch?v=KSsjPbowHQ0&list=PLFAYD0dt5xCymcvacfR4CLB9Pk_9L50gz Previous Lesson: Isolation Forest: A Tree based approach for Outlier Detection : https://youtu.be/kqAxfOPlr1U Earlier Lessons: 1. Build your first ML Project: https://youtu.be/KSsjPbowHQ0 2. How to Formulate ML Problem: https://youtu.be/ygayqatDEDk 3. Setup Python Environment: https://youtu.be/Yk9BFMO6QXE 4. Jupyter Notebook Tutorial: https://youtu.be/4yuo96HtTw8 5. What is ML Modeling: https://youtu.be/Bcfk4HKgC5E 6. Reduce the size of Pandas Dataframe: https://youtu.be/Xa26NB75htg 7. What is EDA: https://youtu.be/rqCZZBrfNak 8. How to impute missing Data: https://youtu.be/Qir0Qi_CD2o 9. Mice Imputation Algorithm: https://youtu.be/BjyUbk258o4 10. How to impute missing data in categorical Variables: https://youtu.be/dm7YNsN_Nwo 11. How to Detect Outliers with Z Score: https://youtu.be/Qv2vCviL4iU 12. Mahalanobis distance: https://youtu.be/YY1lz8cOgH8 13. Cook's Distance: https://youtu.be/PVJYdMjfrAA Let me know in the comments section if you have any questions! If you enjoyed this video, be sure to throw it a like and make sure to subscribe to not miss any future videos! Thanks for watching! #mlmodeling, #python, #machinelearning, #artificialintelligence, #pandas, #datascience