Sahil Vats

Data Science Student with hands-on experience building practical, data-driven systems. Worked on automating tender bid preparation by combining current market rates with historical data, while also structuring data formats to support future analysis. Developed a hybrid deep learning–based movie recommendation system to address the cold start problem using both visual features and rating data from the MovieLens Dataset. Comfortable working with Python, machine learning and data analysis, with a strong focus on applying concepts to real-world problems and improving workflows.