LightGBM Fast Boosting

LightGBM is a gradient boosting library for fast decision tree training. It uses leaf-wise tree growth (growing one leaf at a time, creating deeper trees) instead of level-wise (XGBoost). This makes it 10-20x faster and more memory-efficient. Data scientists use LightGBM for classification (fraud detection, churn prediction) and regression (price forecasting, demand). The library is production-ready: small model size, fast inference, strong accuracy. It's standard in Kaggle competitions and industry ML pipelines.