tensorflow / tensorflow/probability
Logistic factorial analysis example/tutorial
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- Jupyter Notebook
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Description
Contributor guide
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 reviewing the linked Edward example at examples/factor_analysis.py and the existing TensorFlow Probability examples. Determine the intended scope of the logistic factor analysis tutorial and where it belongs in this repository. Done means the example or tutorial is added with an appropriate validation or usage path.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100