Registration for the 2020 SIOP ML Competition
Get ready for the 3rd Annual SIOP Machine Learning Competition. The primary focus of this year's competition will be the optimization of personnel selection systems, balancing the best in machine learning with common constraints. Register to gain access to the competition site and data as soon as it goes live (February 17th). Additional information on the specifics of the challenge will be provided in the coming weeks to those who register.

Why Register?
The competition kaggle-like website (EvalAI) along with access to the data will be provided to those who register. Last year around 450 professionals and students participated. Registration is not commitment but rather signifies that you would like to receive data, site access, and details about the competition. It is your pass to compete.

General Rules:
As a big part of this competition is inclusion and transparency, we want your efforts to be recognized as widely as possible. After the competition we will be open-sourcing all the data on GitHub. Similarly, winning solutions' final syntax must be provided in an open source language and will be hosted on GitHub. Code that cannot reproduce results may result in forfeiture. Lastly, at least one member from the winning teams is expected to attend SIOP to present at the ceremony.

Start date:
The competition starts on 2/17. On that date, we will send those who have registered: 1) detailed instructions, 2) access to the competition website, and 3) access to the data. If that date is in the past, emails will be sent as we can get to them for new registrants.
Email address *
Code Agreement
I understand that my final code will need to be written in open source programming languages, be able to reproduce my final results, and be made public on Github under the MIT license. *
Attendance Agreement
If I am part of the winning solution at least one person from my team will attend the annual SIOP conference in Austin, TX on April 23-25, 2020 (team membership is flexible). *
Additional Info
First name *
Your answer
Last name *
Your answer
Affiliation (school or company)
Your answer
Team members (firstname/lastname/email) each separated by new line. This is optional and team membership can be modified later.
Your answer
Any questions, comments, or concerns?
Your answer
Competition Brought To You By
Nick Koenig & Isaac Thompson
Modern Hire's Principal Data Scientists
A copy of your responses will be emailed to the address you provided.
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