-----------------------------------------ABOUT THE PROJECT----------------------------------------------------

– Developed an independent movie recommendation system utilizing item-based collaborative filtering to enhance recommendation accuracy.

– Implemented advanced vectorization techniques within Natural Language Processing (NLP) to analyze and match movie preferences.

– Expanded the dataset to include over 4,000 movies, integrating Bollywood titles to increase cultural diversity and relevance.

-----------------------------------------STEPS TO RUN MODEL-----------------------------------------------------

USER NEEDS TO RUN THE MOVIE_RECOMMENDATION_SYSTEM (mrs) PYTHON FILE FIRST AND CREATE PICKLE FILES IN THERE SYSTEM. IN THE SAME FOLDER RUN THE APP.PY FILE AFTER THAT ON THE TERMINAL TYPE "streamlit run app.py". USER WILL BE LANDED ON THE WEBPAGE AND IT IS READY TO USE

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