Describe your experience building recommendation systems.

Question

Accepted Answer

A recommendation system suggests items to users based on preferences and behaviors.

Collaborative Filtering: Uses user-item interactions. Example: Netflix recommending shows based on user viewing history.
Content-Based Filtering: Recommends items similar to those a user liked. Example: Spotify suggesting songs based on user playlists.
Hybrid Systems: Combines collaborative and content-based methods. Example: Amazon suggesting products based on browsing and purchase history.
Matrix Factorization: Decomposes user-item interaction matrix to find latent factors. Example: Using Singular Value Decomposition (SVD) for recommendations.
Deep Learning: Utilizes neural networks for complex patterns. Example: Using recurrent neural networks (RNNs) for sequential recommendations.

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