This project is a recipe recommendation system that is designed to solve a very common real-world problem. It uses a combination of data preprocessing, natural language processing (NLP), and vector similarity to suggest recipes based on a user's entered ingredients. The core of the system is a Word2Vec model trained on a dataset of diverse recipes, which is used to find semantic similarities between ingredients.