Projects

Overview A comprehensive movie recommendation system leveraging collaborative filtering and content-based filtering techniques to provide personalized suggestions. The system analyzes user ratings and movie metadata to identify patterns and recommend films tailored to individual preferences. Problem Statement Users searching for new movies often face decision paralysis with thousands of options. A personalized recommendation system can reduce discovery friction by leveraging collective intelligence from user ratings and similarity between movies to surface relevant content....

Overview An end-to-end machine learning pipeline that predicts soccer match outcomes with 72% accuracy using advanced feature engineering, ensemble methods, and hyperparameter optimization. Benchmarked 7 classifiers across 10 dataset variants with rigorous cross-validation. Problem Statement Traditional sports prediction relies on domain expertise and intuition. A systematic ML approach can leverage historical match data to identify patterns and predict outcomes, enabling data-driven insights for analysts and sports enthusiasts. Solution & Approach Engineered a comprehensive pipeline combining:...