Plan of Action
We obtained the open-source Big data movies dataset for this project and used Content-based and Collaborative based recommendations to produce a data frame that can be visualized on a website.
Environment Setup
- Install PyCharm to build the front-end of our website.
- Jupyter Notebook to develop the model for recommendation and python distribution platforms to build the back-end.
- Extract modelled files
Workflow Diagram
● Content-based algorithm activity diagram
● Cosine similarity
References for dataset:
tmdb_5000_credits.csv from Kaggle tmdb_5000_movies.csv from Kaggle Movie_Titles.csv from Grouplens
Kaggle dataset link: https://www.kaggle.com/tmdb/tmdb-movie-metadata?select=tmdb_5000_credits.csv
Group-lens dataset link: https://grouplens.org/datasets/movielens/ framework: https://docs.streamlit.io/
Authors
● @Vishal Solanki ● @Ravleen Kaur ● @Shoaib Ahmed ● @PurveshP0406