Abstract:
As we know, Businesses are increasing day by day and due to this rapid increase, the
people who have a product to sell have a dire need for prediction of the success rate,
keeping this scenario in mind a way in which investors can use their money which can
bring them success. A person who wants to do shopping sometimes doesn’t know
about the outlets quality so this provides a solution in which a person will get to know
about the outlets value through sentiment analysis and choose on customer’s point of
view. Predicting the success of a start-up is commonly defined as two-way strategy
that makes a large amount of money to its founders, investors and first employees with
a focus on how a start-up or an investor could explore all this knowledge for a better
decision making in investment strategy and monetary gain, the study intends, using
scraping tools to scrap the data from the google maps and then by applying algorithms,
to create a predictive model that has to classify whether a start-up is (already)
successful or not. So, in this project we will create web application of machine learning
algorithms to generate success rate. Everybody prefers quality over quantity so that’s
why a sentiment analysis will be done over reviews of any outlet so a person who
doesn’t know about the reputation of an outlet can easily decide
