stackabletech / stackabletech/issues
Evaluate `feathr` for machine learning feature engineering
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Description
This issue will cover a spike with Feathr.
Feathr offers an API et al for defining feature engineering / enrichment in a standardised way. The examples on the website seem to be very Azure-centric so ticket will involve building a simple standalone example of its usage.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the linked Feathr overview and its examples, paying attention to the Azure-specific assumptions. Build a simple standalone example that demonstrates Feathr feature engineering or enrichment outside that context. Done means the example runs independently and clearly shows the API usage.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- machine-learning
- Domain
- data-engineering, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100