Summary
Opening a restaurant in a densely populated city is always challenging and often requires understanding of the current food preferences, location, competition, and the capital investment associated with it.
San Francisco being one of the most populated cities in the US has plethora of restaurants offering different cuisines. Although, offering great food at a lower cost is one of the success metrics, there are external factors that define restaurant’s success. Thus, in order to establish a prosperous business model, it is imperative for a business owner to understand and gauge the restaurant business in and around San Francisco.
Our main objective in this capstone project is to guide the business client in choosing the perfect location to open a restaurant. This project aims to analyze and provide insights on restaurant businesses around SF neighborhoods using unsupervised learning techniques (K-Means Clustering) so that the business owner can make an informed decision.