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Amazon ML Challenge 2025: Ranked Top 0.5% globally (42nd out of 8690 teams). Engineered a multimodal price prediction pipeline using XGBoost, LightGBM, and CatBoost.
This project is an end-to-end deep learning-based text summarization system designed to automatically generate concise and informative summaries from large volumes of textual data.