Hybrid movie recommendation web app using Machine Learning, the movie DB API, and Flask.

Maven project that consists of a book and movie recommendation system based in Apache Mahout artificial intelligence algorithm.

This project implements a robust recommender system for book recommendations, leveraging ensemble methods, user-specific strategies, XGBoost, and extensive data preprocessing to achieve high performance in the Recommender System 2023 Challenge hosted by Kaggle for students of Politecnico di Milano's Recommender Systems course.

Sincere, a less biased hybrid movie recommendation system based on ratings.

Sustainable Recipes. A Food Recipe Sourcing and Recommendation System to Minimize Food Miles

Wedding Package Recomendation API

Anime Recomender System

A simple but fully functioning e-commerce website built with Laravel.

A python project to extract Association Rules from IranITJobs2021 dataset using Apriori algorithm.

Movie Recommendation System using The Movies Dataset on Kaggle.

A system to recommend wines based on their description.

NNMU Detection

Projects developed under the Data Mining II college chair during the 2019/2020 school year

My kaggle Notebooks

Movie Recommender API: FastAPI-based backend for movie recommendations using collaborative filtering.

In this section, we will create a recommendation system on the movie meta dataset.

Implement the K-means and Apriori methods to provide recommendations for the selection of elective courses according to the expertise group.

Scientific paper reviewer recomendation based on a text analysis technique and the bag-of-words concept.

Code for my book recommender application built with Flask