This is a public reupload of the Mines Park Water Treatment project for Baylor University's STA2300 Introduction to Data Science in Spring 2021.
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Processed 43,000+ records with 42 variables, using lubridate for time series manipulation. Visualized key variables like pH levels and membrane permeate flow, identifying a critical fault event. Developed regression models (linear, stepwise) and used Lasso (cv.glmnet) to improve predictive accuracy for pH levels and fault detection.
jshiah/McLennan-County-Wastewater-Treatment-Fault-Predictor
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Processed 43,000+ records with 42 variables, using lubridate for time series manipulation. Visualized key variables like pH levels and membrane permeate flow, identifying a critical fault event. Developed regression models (linear, stepwise) and used Lasso (cv.glmnet) to improve predictive accuracy for pH levels and fault detection.
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