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

Last update: Feb 15, 2022

Overview

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:

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

Demo:

Home UI:

Database structure:

Result UI:

Owner

Prem Jha

https://www.kaggle.com/premjha

GitHub Repository

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

Related tags

Overview

Product-based-recommendation-system

Technology Used in this project:

Demo:

Home UI:

Database structure:

Result UI:

Owner

Prem Jha

PICK: Processing Key Information Extraction from Documents using Improved Graph Learning-Convolutional Networks

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Let Python optimize the best stop loss and take profits for your TradingView strategy.

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