A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity

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:

Batman killer croc takedown figures: nDCG=0.917
Star Wars Movie Heroes Yoda: nDCG=0.942
Harry Potter Hogwarts Bookmarks: nDCG=0.9406

Technology Used in this project:

Pandas
Numpy
Sklearn
MongoDB as Databases
Streamlit for UI

A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity

Technology Used in this project:

Demo:

Home UI:

Database structure:

Result UI:

GitHub