Random Forest Algorithms | Your First Supervised Machine Learning Model

Learn how to train a full Random Forest classifier on the seaborn Titanic dataset using Python, pandas, and scikit-learn in this complete end-to-end machine learning tutorial. This walkthrough shows you exactly how to load and clean real tabular data, build a reproducible preprocessing Pipeline with SimpleImputer and OneHotEncoder, and use a ColumnTransformer to handle missing values and categorical features properly. All of the code and the full Jupyter notebook are available in the GitHub repository: https://github.com/KelvinLinBU/Random_Forest_YT If you find this helpful, please like, comment, share, and subscribe for more tutorials on Python, machine learning, random forests, data science workflows, and software engineering. Shoutout to @dontmakelies for the editing. Check out my book Modern Data: From Ingestion to Production available on Amazon, Apple Books, and Barnes & Nobles: 🔗 Amazon 🚚 : https://www.amazon.com/dp/B0GH8J71SC 🔗 Barnes & Noble 📚: https://www.barnesandnoble.com/w/modern-data-kelvin-lin/1149201590? 🔗 Apple Books 🍎: https://books.apple.com/us/book/modern-data/id6757802062