Neural Collaborative Filtering (NCF) is a technique used in Recommender Systems to make recommendations using a neural network. The goal is to learn a mapping from the user and item embeddings to a score.
**Example:** Given a user-item interaction matrix, train a neural network to make recommendations.
**Constraints:** The user and item embeddings should be learned using a neural network.
Test Cases
Test Case 1
Input:
[[1, 2, 0], [0, 0, 3], [0, 1, 0], [1, 0, 0]]Expected:
[[0.5, 0.5, 0.5], [0.5, 0.5, 0.5], [0.5, 0.5, 0.5], [0.5, 0.5, 0.5]]Test Case 2
Input:
[[0, 1, 0], [1, 0, 1], [0, 1, 0], [1, 0, 1]]Expected:
[[0.5, 0.5, 0.5], [0.5, 0.5, 0.5], [0.5, 0.5, 0.5], [0.5, 0.5, 0.5]]+ 3 hidden test cases