🔱 Some recognized algorithms[Decision Tree, Adaboost, Perceptron, Clustering, Neural network etc. ] of machine learning and pattern recognition are implemented from scratch using python. Data sets are also included to test the algorithms.

Are you confused about what to binge-watch next? Welcome to the Precog-Movie-Recommender. Just enter ratings about 5 movies which we will show you, and we will recommend you what to view next.

Проект создания рекомендательной системы для библиотеки

Restaurants Recommendation System

A model to recommend movies based on collaborative filtering (using ALS algorithm) and perform various analysis on the data.

Collection of my ML projects using PySpark

Exploring Recommendation Systems: Code examples comparing implementations using PySpark (ALS) and TensorFlow Recommenders. Dived into the practical examples and Youtube's case study provided in the README.

May - June 2022

This project is a web application for recommending restaurants using Google Maps data and AI-based recommendations. It allows users to view, rate, and review restaurants, and provides personalized recommendations based on user preferences and reviews.

A powerful recommendation system for Steam games, combining Content-Based and Collaborative Filtering techniques. Built with Python, Scikit-learn, and Streamlit to deliver accurate, real-time game recommendations. Perfect for gamers and data scientists interested in building intelligent recommendation engines.