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The project aims to create movie recommendation system with algorithms, including content-based, popularity-based, and collaborative filtering methods. Data of over 4800 movies is used.
a keyword analysis tool/API in flask: extracts keywords from e-commerce items in different categories and provides keywords/price distribution information with user’s feedback input;
Code of the shiny-app MH-shiny from: Volcanic-associated ecosystems of the Mediterranean Sea: a Systematic Map and an Interactive Tool to support their conservation
This project uses the Tweepy library to extract tweets off twitter according to a particular keyword and performs sentiment analysis on the fetched tweets. The machine learning model was trained on the SMILE twitter emotion dataset.