Develop Sentiment Analysis, Topic Modeling, and Text Classification Modules
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 20/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- python, scikit-learn
- Domain
- data, machine-learning
Research direction
The issue names no files, tests, or entry points to begin with. First review the toolkit's existing components and determine the intended interfaces for sentiment analysis, topic modeling, and text classification; completion requires robust, scalable modules that integrate with the other toolkit components.
Written by the indexing model from the issue text.
Description
Create robust modules for sentiment analysis, topic modeling, and text classification. Ensure these modules are scalable and integrate seamlessly with other toolkit components.
- Dominant language
- Jupyter Notebook
- Stars
- 7
- Forks
- 4
- PR merge metrics
- No merged PRs in 30d
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.
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