Day 22: Recommender System with Matrix Factorization

Описание к видео Day 22: Recommender System with Matrix Factorization

Today, I built a Recommender System using Matrix Factorization to predict how users will rate items they haven’t interacted with. I used Singular Value Decomposition (SVD), a popular matrix factorization technique, to decompose the user-item interaction matrix and predict missing ratings. The goal was to recommend movies to users by predicting the ratings they might give to movies they haven’t watched yet.

If you want to see the code, you can find it here: [GIT REPO](https://github.com/saxenaakansha30/30....

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