/Recommender_System

A Python implementation of Collaborative Filtering algorithms used in Recommender Systems

Primary LanguageJupyter Notebook

Recommender System

Part 1: SVD&SVD++

  • Implemented SVD and SVD++ using Multiplicative update rules
  • Used KL divergence and Euclidean distance to compute cost, respectively.

Part 2: Movie Recommender

  • Developed a recommender system based on the SVD++ algorithm to predict users’ preferences for unseen movies based on their similarity to other users

  • The dataset contains 100,000 ratings from 1000 users on 1700 movies. Data Source: https://grouplens.org/datasets/movielens/100k/