The problem statement "content recommendation sytem" caught our attention more and inspired us to generate a more interactive and responsive user interface Recommendation system is build to generate recommendations for particular movies according to users interest and latest updates. We used python and its libraries for creating the backend of the systems. For frontend we have used web technologies which creates an interactive layout for user. we have used flask and jinja technique to integrate backend with frontend. We were not familiar with AI-ML ,so we tried to figure different ways to make our website interactive and responsive. We learned to work under pressure and got to know industrial standards of our field. we leraned some new technologies - python libraries and flask . we will be improvising more on categorization of data which would recommend movies more accurately and precisely.
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