This project aims to use AI, machine learning, deep learning, and web scraping to develop a system that rates spoilers on a scale of 1 to 10 for movies and TV shows from streaming services like Netflix and Amazon Prime. The purpose is to provide viewers with a more personalized and efficient viewing experience by allowing them to make more informed decisions about what to watch and what to avoid. The system also uses a recommendation system to suggest movies and TV shows based on the viewer's preferences. The project addresses challenges such as collecting data from streaming services and developing a spoiler scale that accurately represents the impact of spoilers on the viewing experience.
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This project uses AI, ML, web scraping to rate spoilers on a 1-10 scale for TV shows and movies from streaming services. It aims to help viewers make informed choices and offers recommendations based on preferences, addressing challenges such as data collection and spoiler scale accuracy.
ayushjain01/Mini-Project
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This project uses AI, ML, web scraping to rate spoilers on a 1-10 scale for TV shows and movies from streaming services. It aims to help viewers make informed choices and offers recommendations based on preferences, addressing challenges such as data collection and spoiler scale accuracy.
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