Entrepreneurship is difficult but extremely rewarding. Ensuring business starts in the right location, with the right demand and resources is instrumental to success. Our goal was to utilize lots of the data resources we were given at VThacks to help the business world thrive, and therefore help the U.S. economy.
What it does
It allows a user to input their current wealth, market they wish to enter, and desired locations for business. It then runs machine learning algorithms using various API's to determine the best locations for the price (depending on real-estate in the area) that the owner can afford.
How we built it
Scraped data from city-data.com of every city in the US for population, median income, cost of living, etc. using python. Used Nessie API to get sample merchants and categories and linked them to locations Use YELP API to get merchants and categories linked to locations Cleaned all data set and merged together in Google data lab. Use google cloud functions to create machine learning model of best options,. Create flask app and hosted on Google Cloud Engine Used micro strategy for data visualization images should on app
Challenges we ran into
IP's continuously blocked for mining data. Had to download VPN to confuse screening.
Accomplishments that we're proud of
Incredible machine model that will really help small businesses Used a large number of data sets and synced them all successfully Scraped large amount of data despite complications Attractive interface that is easy to navigate
What we learned
How to build machine models, good tools for data visualization, how to build a flask app and host it to google cloud
What's next for DataBiz
Get more data to make model more accurate