This is a project from the course [T81-855: Applications of Deep Learning at Washington University in St. Louis](https://sites.wustl.edu/jeffheaton/t81-558/). All students must create a Kaggle account and submit a solution. If you are a student, once you have submitted your solution entry log into Canvas (at WUSTL) and submit a single file telling me your Kaggle name on the leaderboard (you do not need to register to Kaggle with your real name). This competition will be visible to the public, so there may be non-student submissions as well as student.

This competition see if you can predict a "business score" for each of the USA zipcodes.  The exact nature of the "business score" (score column) is not disclosed.  It is connected to the business/market saturation of a zipcode.  The data files given to you on Kaggle will not be sufficient to predict.  You must augment your data with additional files.  Some suggestions include:

<ul>
<li><a href="https://www.irs.gov/statistics/soi-tax-stats-individual-income-tax-statistics-2016-zip-code-data-soi">US Government public data for "SOI Tax Stats - Individual Income Tax Statistics"</a>
<li><a href="https://www.data.gov/">Data.GOV: The home of the U.S. Government’s open data</a>
</ul>

[This video][1] describes the competition.


  [1]: https://www.youtube.com/watch?v=GaKo-9c532c