This project is a skincare recommendation system that uses webcam detection, image analysis, or manual input to identify skin concerns and suggest suitable products from a dataset.

DeepShelf is your AI-powered book buddy 📚🤖 — type what you’re in the mood for, and it finds the perfect novel using smart search + ranking ✨🔍

FRUDRERA is an AI-powered recipe recommender that suggests recipes based on the ingredients detected in a photo of your fridge. It utilizes object detection and OCR to identify ingredients and recommend recipes accordingly.

This project was done to fulfil the Machine Learning Terapan 2nd assignment submission on Dicoding. The domain used in this project is book recommendation.

SOEN471 Project - Team 10 - Winter 2024

An AI-based inventory optimization system that leverages machine learning to predict demand, recommend menu items, and streamline stock management for restaurants and food service businesses.. — all deployed through a real-time Stream lit web app.

A Multi-Agent Deep Reinforcement Learning (MARL) based system that recommends research papers based on user-selected categories. Multiple DQN-trained agents collaboratively learn optimal policies to suggest relevant and diverse papers tailored to user preferences.

MovieMinds - Connect with similar cinephiles

All-in-one stealth OSINT reconnaissance tool for threat intel, bug bounty, and red teamers. metadata extraction, and parameter fuzzing included.

Creating an Product Recommender System with Apriori and FPGrowth.

A composition of Machine Learning Projects in python using algorithms in supervised, unsupervised, and deep learning.

Recommending osu! beatmaps for you

Diet Recommendation System using KNN and built with Python for backend, ReactJS for frontend, and Docker for fast deployment.

M.Sc. Courses in Data Science, including Machine Learning, Deep Learning, Statistics and Data Analysis, and Recommendation Systems.

This is a collaborative filtering based books recommender system & a streamlit web application that can recommend various kinds of similar books based on an user interest.

An overview of reccomendation systems in Python

4Geeks Academy data science boot camp: movie recommender system with project

제12회 산업통상자원부 공공데이터 활용 아이디어 공모전 최우수상🏆 | LLM 프롬프트 엔지니어링 | 추천 시스템 | 자연어 처리

Simple and interpretable recommender system using cosine similarity between movie vectors.

Conducted Market Basket Analysis (MBA) on Amazon product dataset to enhance recommendations. Identified top-selling products and top products in each category using review count. Implemented asso- ciation rule mining for personalized recommendations. Evaluated effectiveness through metrics.