{"adoption": {"forks": 123, "observed_at": "2026-08-28T04:03:30.817225+00:00", "stars": 1081}, "canonical_url": "https://ross.abutalabs.com/products/conformal-prediction", "card": {"archived": false, "artifact_type": "learning-resource", "description": "Lightweight, useful implementation of conformal prediction on real data.", "domain": ["machine-learning", "data-science", "tutorials"], "enriched": true, "function": ["machine-learning", "data-science", "nlp", "computer-vision"], "health_score": 51, "homepage": "http://people.eecs.berkeley.edu/~angelopoulos/blog/posts/gentle-intro/", "language": "Jupyter Notebook", "license": "MIT", "license_family": "permissive", "maturity": "active", "member_repos": ["aangelopoulos/conformal-prediction"], "name": "aangelopoulos/conformal-prediction", "platform": ["python"], "pushed_at": "2025-11-14T09:33:36+00:00", "repo": "aangelopoulos/conformal-prediction", "stars": 1081, "tags": ["conformal-prediction", "uncertainty-quantification", "jupyter-notebooks", "prediction-sets", "distribution-shift", "time-series-forecasting", "statistics"], "topics": ["computer-vision", "conformal", "conformal-prediction", "distribution-shift", "natural-language-processing", "time-series", "time-series-prediction", "uncertainty", "uncertainty-estimation", "uncertainty-quantification", "conformal-inference"], "urls": [], "use_cases": ["learn conformal prediction with real examples", "build prediction sets with coverage guarantees", "quantify uncertainty in machine learning models", "apply conformalized quantile regression for prediction intervals", "experiment with uncertainty estimation under distribution shift", "prototype new conformal prediction methods"], "what_it_is": "A collection of Jupyter notebooks demonstrating conformal prediction (conformal inference) on real-world machine learning tasks like image classification, regression, and time series. It serves as both a practical tutorial and a template sandbox for developing uncertainty quantification methods without needing to run the underlying models.", "when_to_avoid": ["you need a production-ready conformal prediction library with an API", "you want a maintained pip-installable package rather than notebooks", "your task is unrelated to statistical uncertainty estimation"], "when_to_choose": ["you want to learn or teach conformal prediction hands-on", "you need statistically guaranteed prediction sets or intervals", "you want notebook templates for uncertainty quantification research"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/conformal-prediction", "repo": "aangelopoulos/conformal-prediction", "role": "main", "score": 56}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:03:30.817225+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T06:51:19.229201+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "4778ea8e89a47736fa392d353cef2e3185a3dc41f24badf7ff40525f014869b7", "fetched_at": "2026-08-28T04:03:30.817225+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aangelopoulos/conformal-prediction"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 52, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 1713, "days_push": 292, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 56, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}