als-algorithm

🔱 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.

Проект создания рекомендательной системы для библиотеки

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.

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

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.

Restaurants Recommendation System

Collection of my ML projects using PySpark

A collaborative filtering recommender system

Système de recommandation de films comparant les algorithmes ALS et SVD Implémentation manuelle d'ALS vs SVD de scikit-surprise sur le dataset MovieLens

Built a movie recommender system in PySpark/Databricks, benchmarking popularity baselines, collaborative filtering (item- and user-based cosine similarity), and ALS matrix factorization (explicit and implicit) against each other with rigorous train/val/test evaluation. Extended the project with Jaccard similarity and MinHash-based market seg.

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.

🔍 Analyze large datasets using the ALS algorithm for predictive modeling and improve recommendations in various applications.