Ling Shou Dian Shang Ke Hu Liu Shi Mo Xing ,Ji Yu tensorflow,xgboost4j-spark,spark-mlShi Xian LR,FM,GBDT,RF,Jin Xing Mo Xing Xiao Guo Dui Bi ,Chi Xian /Zai Xian Bu Shu Fang Shi Zong Jie
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Updated
Sep 5, 2023 - Python
Ling Shou Dian Shang Ke Hu Liu Shi Mo Xing ,Ji Yu tensorflow,xgboost4j-spark,spark-mlShi Xian LR,FM,GBDT,RF,Jin Xing Mo Xing Xiao Guo Dui Bi ,Chi Xian /Zai Xian Bu Shu Fang Shi Zong Jie
xgboost in python and pyspark (using py4j to call jvm-packages)
Predict customer churn in telecom using machine learning to enhance retention strategies and drive better business outcomes.
Predict customer churn using a synthetic dataset with advanced models and metrics to enhance business retention strategies and decision-making.
Predict customer churn using machine learning to identify key factors, helping businesses retain clients through data-driven insights.
Predict customer churn with machine learning to enhance retention strategies and drive business growth through actionable insights.
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