** XGBoost Revolutionizes Machine Learning with Efficient and Scalable Gradient Boosting

XGBoost, a powerful machine learning library, has become a go-to tool for data scientists worldwide. Developed by Tianqi Chen in the early 2010s, XGBoost is built on top of the popular Gradient Boosting framework, which combines multiple decision trees to create a predictive model. Tianqi's innovations, including parallelization, regularization, sparsity-aware optimization, and hardware optimization, make XGBoost faster, more efficient, and scalable.

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Source: https://dev.to/aashwinkumar/the-story-of-xgboost-a-machine-learning-revolution-bib