This project presents data-driven solutions to optimize departmental operations in Human Resources, Marketing, Sales, Operations, and Public Relations. The project addresses key business challenges and enhances decision-making by leveraging machine learning, deep learning, and advanced analytics.
In the Human Resources Department, Logistic Regression, Random Forest, and Deep Learning models are used to predict employee turnover, providing actionable insights for retention strategies. The Marketing Department leverages K-Means, PCA, and Autoencoders for customer segmentation, enabling more targeted campaigns. In Sales, time series forecasting with Facebook Prophet helps predict daily sales, ensuring efficient inventory management. The Operations Department employs deep learning models for chest disease detection, enhancing medical diagnostics. Finally, the Public Relations Department applies Naive Bayes and Logistic Regression to predict customer satisfaction and improve engagement strategies.