This repository provides implementations of three neural collaborative filtering models: Generalized Matrix Factorization (GMF), Multi-Layer Perceptron (MLP), and Neural Matrix Factorization (NeuMF). The models use deep learning to learn user-item interaction patterns from implicit feedback data. Built with Keras and Theano, the implementation optimizes models using log loss with negative sampling for ranking tasks.