Deep learning based Recommendation Techniques

In this work we try to explore different ways of building recommender systems. We check on the baseline methods and how they work, then we try using deep learning neural networks to build up efficient recommenders. We address two types of recom- menders, rate estimators, and session-based recommenders. Therefore, we Introduce using fully connected layers to estimate ratings of user and item pairs based on their embedded vectors