In this video, we explain the Light Gradient Boosting Machine (LightGBM)
algorithm from scratch with complete mathematical and statistical foundations.
This tutorial explains how LightGBM works internally, including:
✔ Boosting and additive tree models
✔ Leaf-wise tree growth strategy
✔ Histogram-based split finding (mathematical intuition)
✔ Gradient and Hessian usage in LightGBM
✔ Gain calculation and split criteria
✔ LightGBM Classifier vs Regressor
✔ Why LightGBM is faster and more memory-efficient
✔ Bias–Variance tradeoff and overfitting control
This video is ideal for:
- Machine Learning beginners
- Data Science students
- Python developers entering ML
- Interview preparation (ML / AI / Data Science roles)
This tutorial is part of the playlist:
🎯 Machine Learning Algorithms – From Scratch with Math
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