Gastro Genius

Abstract

Food is essential for human survival, and people are constantly eager to try new, inventive meals. Completing recipes requires careful consideration of taste, smell, and texture to provide optimal results. Many people buy food from unfamiliar grocery stores. It's important to know which ingredients work well together to make a delicious meal. We may build a meal by combining various elements. It is quite difficult for a beginner cook to select the right recipe from a choice of options. Even specialists may struggle. Several websites and research are promoting culinary recipes. Many websites provide cooking instructions depending on the recipe's entry date. Access frequency, also known as user reviews. Machine learning is regularly applied in our daily lives. For example, image processing may be used to recognize objects. Traditional techniques, notwithstanding the variety of food products included, can lead to an increased danger of mistake. Deep learning and machine learning approaches can address these challenges. Data mining and machine learning are becoming increasingly important in analysing and modelling food consumption due to increased availability of data in online databases. In this project, I developed a model to recognize food components and an algorithm to recommend meals based on these elements. In this project, I developed a mobile recipe suggestion system that recognizes items and creates corresponding recipes. The machine learning model generates recipes based on TF-IDF and Cosine Similarity. The program displays top recipes and uses image recognition to identify items.