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XGBoost Model for Machine Learning implementation on breast cancer dataset in Python and churm modelling in R

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XGBoost-for-Machine-Learning

XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way.

This Code will guide you on using XGBoost in Python and R programmimg. XGBoost Model implementation on two datasets; breast cancer dataset in Python and in churm modelling in R

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XGBoost Model for Machine Learning implementation on breast cancer dataset in Python and churm modelling in R

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