Machine learning recommendations are based on keywords, user activity, and other similar measures that help us define what a person may like. But they become ineffective if the user preference involves thousands of filters and subjective criteria that are specific to the user. So here, we discuss Natural Language Processing recommendation systems. Based on our previous experience, we’ll outline the general idea and limitations of this model, and explain some of the best approaches for how to build a NLP-based recommender system.