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HARTA DINAMICA
WQD7004 Group Project Final
Bryan Chak Yen Hou (24078819)
Raynaldo Franciscus (24073666)
Dhanasree Seelam (23077229)
Muhamad Danial bin Khalid (24079013)
Predicting Wine Quality Using Chemical Attributes
This report is based on a white wine dataset and uses regression and classification models to predict and analyze wine quality. Through EDA, the main physical and chemical attributes are explored, and linear regression, logistic regression, and random forest models are constructed. Finally, the model performance is evaluated and summarized to identify the key factors affecting wine quality.
Dual-Model Approach to HR Analytics: Employee Attrition and Income Prediction
A project from WQD7004 Programming For Data Science in Universiti Malaya
