Abstract : Two important chapters of the book are laid out in this chapter, each of which focuses on a different aspect of the machine learning landscape. The basics of the Scikit-Learn library are explained in Introduction to Scikit-Learn. It functions as a flexible and simple tool for both inexperienced and seasoned machine learning practitioners. This chapter examines the functions of Scikit-Learn in supervised and unsupervised learning while emphasizing its practical applications. The book XGBoost and LightGBM - Boosting to Excellence explores gradient boosting, an ensemble learning method renowned for its accuracy in making predictions. These libraries are broken down to show their special qualities, benefits, and practical uses. To help readers choose the best tool for their particular projects, a comparison of XGBoost and LightGBM is also provided
Cite : Gouri, M. H., & Kumar, M. (2023). Empowering Machine Learning With Scikit-Learn, Xgboost And Lightgbm (1st ed., p. 1). Noble Science Press. https://doi.org/10.52458/9789388996747.nsp2023.eb.ch-01
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