This repository consists of code and datasets used to built a book recommender system using collaborative filtering.

It's a website that recommends books from database to users based on ratings given by other users. Two recommender models are built viz. 1) Popularity Based Recommender 2) Using Collaborative Filtering Algorithm

The RECeSS (Robust Explainable Controllable Standard for drug Screening) project is funded by a Marie Skłodowska-Curie Postdoctoral Fellowship 2022.

Recommender system for IBM Watson public articles

A movie recommendation site made using Django

Recommendations with IBM Data (knowledge-based plus collaborative filtering both model-based and neighborhood-based)

In this machine learning project, we build a recommendation system from the ground up to suggest movies to the user based on his/her preferences.

Jupyter notebook file with recommendation methods for articles to users of the IBM Watson Studio platform.

Recommender system using Popularity based and Collaborative based filtering

Build a recommendation system using IBM Watson Studio platform.

NextRead is a book recommender system built for Book Lovers. Simply enter your current favourite book and get peronalized book list to find your new favourite.

Recommender system from Yelp dataset

Articles recomendations for IBM Watson users

Analyzed the interactions that users have with articles on the IBM Watson Studio platform, and made recommendations to them about new articles they will like

Trend Fitness is a web application dedicated to providing professional fitness advice which will include a range from fitness plans to diet plans catered to every individual needs. I believe that my web application will embark on a transformative journey towards a healthier lifestyle.