LightGBM and awesome-gradient-boosting-papers
One is a high-performance gradient boosting framework for machine learning tasks, and the other is a curated list of research papers about gradient boosting with implementations, making them complements where the latter can inform the use and development related to the former.
About LightGBM
lightgbm-org/LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
LightGBM is a powerful tool for anyone building predictive models. It takes your raw data, learns patterns from it, and generates highly accurate predictions for tasks like ranking items, classifying customers, or forecasting trends. Data scientists and machine learning engineers use LightGBM to quickly develop high-performing models, even with very large datasets.
About awesome-gradient-boosting-papers
benedekrozemberczki/awesome-gradient-boosting-papers
A curated list of gradient boosting research papers with implementations.
This list provides a comprehensive collection of research papers and their accompanying code implementations specifically focused on gradient and adaptive boosting techniques. It helps researchers and practitioners in various AI fields stay updated on the latest advancements and reproduce results. You can find papers from top conferences in machine learning, computer vision, natural language processing, and data science, making it a valuable resource for those building or studying advanced predictive models.
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