@datascibykashi: Today, we dive into Random Forest, a powerful ensemble ML technique, and explore the OOB (Out-of-Bag) score, which lets us estimate model accuracy without a separate test set. 💻❤️ 💡 In this video: 1️⃣ Building a Random Forest model from scratch on a Heart Disease dataset. 2️⃣ Understanding OOB score and how it validates the model internally. 3️⃣ Visualizing feature importance to see which health factors matter most. 4️⃣ Tips for improving model accuracy and real-world applications. ❓ Comment below: What feature do you think is the most important for predicting heart disease? I’ll check and reply to the top answers! 📊 Perfect for anyone learning Python, ML, or Data Science and wants to practice coding with real health data. 🔥 Don’t forget to like, share, and follow for more daily coding tutorials and ML insights! #LearnCoding #DataScience #machinelearning #RandomForest #heartdiseaseprediction

Data Scientist | Kashi

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Tuesday 09 December 2025 14:31:09 GMT