Product-based-recommendation-system
A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity and also uses MongoDB as a database which stores the user data for a semi-collaborative filtering.
Accuracy :
Calculated accuracy using nDCG.
Some randomly selected product efficiency:
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Batman killer croc takedown figures: nDCG=0.917
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Star Wars Movie Heroes Yoda: nDCG=0.942
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Harry Potter Hogwarts Bookmarks: nDCG=0.9406
Technology Used in this project:
- Pandas
- Numpy
- Sklearn
- MongoDB as Databases
- Streamlit for UI