Implementing Machine Learning and Data Mining Techniques for Business Intelligence

This project aims to implement machine learning and data mining techniques for business intelligence using the Weka application. The dataset is analyzed using 10 different data mining techniques, and the performance is evaluated through practical assignments and visualizations. The clustering technique of K-means is implemented, and the data is visualized using classifiers. The dataset is also analyzed using content-based filtering and time series forecasting. The subject, course code, course name, and college/university are not mentioned.