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:

1. Batman killer croc takedown figures: nDCG=0.917

2. Star Wars Movie Heroes Yoda: nDCG=0.942

3. Harry Potter Hogwarts Bookmarks: nDCG=0.9406

Technology Used in this project:

1. Pandas
2. Numpy
3. Sklearn
4. MongoDB as Databases
5. Streamlit for UI

Demo:

Home UI:

Database structure:

Result UI: