The most effective tool any restaurant can have is the capability to track the daily sales of their food and beverage. Currently, recommendation systems plays an important role in both academia and industry. These are very helpful to manage an overload of information. In this paper, applied machine learning techniques for user reviews were used and valuable information in the reviews were analyzed. For both the customers and the owners, reviews are useful to make data-driven decisions. We built a machine learning model with Natural Language Processing techniques which captures a user’s opinions from user’s reviews. A lot of businesses fail due to the lack of profit and a lack of proper improvement measures. Mostly, restaurant owners face a lot of difficulties to enhance their productivity.
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