Earn bragging rights (plus a $2000 award!) when you share your data science project on Kaggle and are chosen as our Kernel Author of the Month!
Topics:
[color=rgba(0, 0, 0, 0.7)]We're launching a new award for Kaggle contributors: Kernel Author of the Month. Each month, we'll recognize one person for creating the best, brightest or most useful new kernel on a specific topic. To be eligible, you must publish an original kernel on that monthly topic.
[color=rgba(0, 0, 0, 0.7)] The first three topics are:
Some see machine learning models as "black boxes" that are difficult to interpret and explain. For this challenge, you're encouraged to use concepts such as feature importance, perturbation importance, and partial dependence plots to explain the predictions of an ML model.
Many data projects benefit from having continuously updated datasets. Can you take advantage of this newly-released feature and share a novel use case with the world?
Kaggle has thousands of datasets that can be used to tell stories and to answer questions concerning the way that people interact. Can you think of a way to use an auto-updating dataset and a model explainability tool to tell a story relating to the topics of sociology or economics?
[color=rgba(0, 0, 0, 0.7)]How to Enter:
Each month will have its own new tag that must be added to your kernel to make it eligible for the award. Submissions must be new and original kernels on the monthly topic.
[color=rgba(0, 0, 0, 0.7)]February 2019: ML Model Explainability Explain the output of a ML model and add the tag “model explainability”
[color=rgba(0, 0, 0, 0.7)]March 2019: Usefulness of Auto-Updating Datasets Use a dataset where the “auto-update” setting is enabled and add the tag “auto-updating data”
[color=rgba(0, 0, 0, 0.7)]April 2019: Sociology and Economics Focus on the subject(s) of sociology and/or economics and add the tag(s) “economics”/ “sociology”
If you are selected as an awardee, you may choose to accept or reject the award. If you accept the award, you certify that you comply with the following eligibility requirements.
To be eligible to win a Dataset Award, you must be:
• A registered account holder at Kaggle.com;
• The older of 18 years old or the age of majority in your jurisdiction of residence;
• Not a resident of Crimea, Cuba, Iran, Syria, North Korea, or Sudan.
If you are entering as a representative of a company, educational institution or other legal entity, or on behalf of your employer, these rules are binding on you, individually, and/or the entity you represent or are an employee. If you are acting within the scope of your employment, as an employee, contractor, or agent of another party, you warrant that such party has full knowledge of your actions and has consented thereto, including your potential receipt of a prize. You further warrant that your actions do not violate your employer’s or entity’s policies and procedures.
In accepting a prize you acknowledge that the awarded material does not (i) infringe any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations; or (ii) otherwise violates any applicable state or federal law.
Unfortunately employees, interns, contractors, officers and directors of Kaggle Inc., and their parent companies, are not eligible to win any Awards.
Share your data science projects on Kaggle for the opportunity to be recognized as Kaggle’s Kernel Author of the Month and receive a $2,000 award!