530.530. DeepFM Model

DeepFM is a deep learning-based model for recommender systems. It combines the strengths of factorization machines and deep neural networks to predict user preferences. We have a dataset of user-item interactions, where each interaction is represented as a tuple of user ID, item ID, and click status (1 for clicked, 0 for not clicked). We want to train a DeepFM model to predict the CTR for each interaction in the dataset.

Example:

We have the following dataset:

user_item_interactions = [(1, 1, 1), (1, 2, 0), (2, 1, 1), (2, 3, 0), (3, 1, 1), (3, 2, 0), (3, 4, 1), (4, 1, 0), (4, 2, 1), (4, 3, 0)]

Constraints:

Write a function to train a DeepFM model to predict the CTR for each interaction in the dataset.