The inspiration for this application comes from using sentiment analysis on the data provided by CoStar Group.

What it does

The application uses sentiment analysis to analyze the provided data, then using additional data, the application provides further analysis of the location(s) described in the data.

How we built it

The application is built using Python and Flask, with JQuery/JavaScript for the front end.

Challenges we ran into

The first challenge the team encounter was having a consistent development environment across different laptops. To over come this, the team implemented Docker for containerization. The next challenge the team encounter was data scraping for the additional information. The team was frequently blacklisted from sites we were trying to scrape; we overcame this challenge by breaking up the scraping amongst the team, and were able to get the required data.

Accomplishments that we're proud of

The team is proud of implementing sentiment analysis and completing a working demo of the application.

What we learned

The team learned that even the simplest machine learning algorithms are hard to implement properly on a short time frame.

What's next for Office Real Estate Analysis

Next steps for the application include gather additional data to provide more accurate reports and develop a mobile version of the application.

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