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feat: add hyperopt to Machine Learning > Hyperparameter Optimization
Co-Authored-By: Claude <noreply@anthropic.com>
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@@ -224,6 +224,7 @@ _Libraries for Machine Learning. Also see [awesome-machine-learning](https://git
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- [timesfm](https://github.com/google-research/timesfm) - A pretrained foundation model from Google Research for time-series forecasting, with non-commercial default weights.
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- Hyperparameter Optimization
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- [optuna](https://github.com/optuna/optuna) - A hyperparameter optimization framework with define-by-run search spaces and pruning of unpromising trials.
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- [hyperopt](https://github.com/hyperopt/hyperopt) - Distributed asynchronous hyperparameter optimization with Tree-structured Parzen Estimators.
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### Natural Language Processing
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@@ -40,6 +40,7 @@ Entries admitted as challengers without adoption-trajectory evidence, by maintai
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- seleniumbase -- admitted 2026-08-16 (PR #3284) as a Browser Automation challenger. It wraps selenium, the successor trajectory in the use case belongs to playwright, and its distinct value is its stealth/UC mode. Admitted because that stealth value counts toward Browser Automation.
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- semantica -- kept 2026-10-01 in the AI and Agents audit as a Data Layer challenger at 16,582 downloads/month on ClickPy, with no adoption-trajectory evidence found. Kept by maintainer decision.
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- jev-ultrafast -- kept 2026-09-24 as a Web Scraping Frameworks challenger, recorded 2026-10-02. Admitted while the repo was under a month old and not on PyPI, so it has no download signal and no adoption-trajectory evidence; its README calls it an MVP and it needs a hosted TypeSafe API key. Kept by maintainer decision.
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- hyperopt -- admitted 2026-10-16 as a Hyperparameter Optimization challenger at 1,793,872 downloads/month on ClickPy. Its 0.3.0 release came after a 4.5-year gap and it has no adoption-trajectory evidence. Admitted by maintainer decision.
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### Cap Exceptions
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