Details
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Umbrella
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Status: Resolved
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Major
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Resolution: Incomplete
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None
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None
Description
This is an umbrella JIRA to track some fun tasks 
We have built many features under the ML pipeline API, and we want to see how it works on real-world datasets, e.g., Kaggle competition datasets (https://www.kaggle.com/competitions). We want to invite community members to help test. The goal is NOT to win the competitions but to provide code examples and to find out missing features and other issues to help shape the roadmap.
For people who are interested, please do the following:
1. Create a subtask (or leave a comment if you cannot create a subtask) to claim a Kaggle dataset.
2. Use the ML pipeline API to build and tune an ML pipeline that works for the Kaggle dataset.
3. Paste the code to gist (https://gist.github.com/) and provide the link here.
4. Report missing features, issues, running times, and accuracy.
Attachments
1.
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San Francisco Crime Classification |
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Resolved | Kai |
2.
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Springleaf Marketing Response |
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Closed | Yanbo Liang |
3.
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Criteo Display Advertising Challenge |
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Resolved | Unassigned |
4.
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Avito Context Ad Clicks |
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Resolved | Unassigned |
5.
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What's cooking classification |
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Resolved | Xusen Yin |
6.
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Click-Through Rate Prediction |
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Resolved | Unassigned |