A memory efficient DLRM training solution using ColossalAI

This project presents a robust machine learning solution to predict KCET (Karnataka Common Entrance Test) ranks based on marks and provide personalized college recommendations. The system aids students in estimating their competitive rank prior to official results and assists in selecting suitable colleges based on predicted ranks and branch.

Third Assignment in 'Artificial Intelligence' course by Dr. Ram Meshulam at Bar-Ilan University

Research thesis on digital law completed in 2021

A collaborative filtering approach using Restricted Boltzmann Machines (RBMs) for movie recommendation based on the MovieLens 100k dataset. Includes data preprocessing, training with CD-k and Parallel Tempering, and evaluation of model performance.

This repository contains final project materials of Machine Learning course in EE Department at Sharif Uni. of Tech. This is a Movie Recommendation System based on K-Means Clustering and Matrix Factorization Algorithms.

Anime Recommendation System

An experiment of a mainstream recommendation system, implementing the entire process and detailed interpretation of related algorithms.

A comprehensive collection of movie recommendation engines designed to provide personalized suggestions and identify trending content based on historical movie data.

A production-grade, containerized hybrid recommendation engine using Weighted Matrix Factorization (ALS) and Context-Aware fallbacks (Country+Platform) to solve the cold-start problem in mobile app engagement.

This is an restaurant recommandation application with customized food note, you can find what to eat with powerful AI assistant in this app

Full-stack activity discovery and outing-planning platform for Casablanca with structured venue data, deterministic recommendations, an Express/Supabase backend, security hardening, and CI-tested workflows.

CareerAI is a full-stack ML web app that analyzes aptitude and performance inputs to recommend the top 5 suitable career paths with confidence scores, using a Gradient Boosting model served through a Flask backend and a responsive frontend.

Machine Learning and NLP models for improving text-based recommendations on TripAdvisor, using BM25, TF-IDF, embeddings, and a Hybrid approach.

An AI-powered personalized learning recommendation system structured for IEEE research submission.