{"adoption": {"forks": 386, "observed_at": "2026-08-28T04:03:13.994754+00:00", "stars": 1014}, "canonical_url": "https://ross.abutalabs.com/products/nlp-notebooks", "card": {"archived": false, "artifact_type": "learning-resource", "description": "A collection of notebooks for Natural Language Processing from NLP Town", "domain": ["machine-learning", "tutorials", "artificial-intelligence"], "enriched": true, "function": ["nlp", "machine-learning", "deep-learning"], "health_score": 20, "homepage": "http://www.nlp.town", "language": "Jupyter Notebook", "license": null, "license_family": "other", "maturity": "maintenance", "member_repos": ["nlptown/nlp-notebooks"], "name": "nlptown/nlp-notebooks", "platform": ["python", "cross-platform"], "pushed_at": "2024-07-16T07:04:02+00:00", "repo": "nlptown/nlp-notebooks", "stars": 1014, "tags": ["jupyter-notebooks", "word-embeddings", "bert", "text-classification", "named-entity-recognition", "topic-modeling", "spacy", "pytorch", "sentence-similarity", "natural-language-processing"], "topics": ["natural-language-processing", "text-mining", "deep-learning", "artificial-intelligence", "nlp", "word-embeddings"], "urls": [], "use_cases": ["learn word embeddings for NLP", "train a BERT text classifier in PyTorch", "build a named entity recognition model with spaCy or CRFs", "do topic modeling with LDA on a text corpus", "compute sentence similarity with embeddings", "learn multilingual and cross-lingual transfer learning", "try zero-shot text classification", "fine-tune transformers for sequence labelling"], "what_it_is": "A collection of Jupyter notebooks covering practical Natural Language Processing topics, from word embeddings and topic modeling to BERT-based text classification and named entity recognition. It is published by NLP Town as an educational resource accompanying their NLP consultancy and workshops.", "when_to_avoid": ["you need a production-ready NLP library rather than tutorial notebooks", "you expect maintained code with a license, tests, or releases", "you need up-to-date coverage of modern LLM tooling, as content skews to pre-LLM-era techniques"], "when_to_choose": ["you want hands-on, runnable notebooks to learn practical NLP techniques", "you need worked examples spanning classical ML (scikit-learn, LDA) and deep learning (BERT, BiLSTM) approaches", "you are preparing NLP training material or self-studying text mining"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/nlp-notebooks", "repo": "nlptown/nlp-notebooks", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:03:13.994754+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T07:11:34.720774+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "da1aed3345e58c125720b64776e4119f6a2bd2f7316526c73f2b9db274002c05", "fetched_at": "2026-08-28T04:03:13.994754+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nlptown/nlp-notebooks"}, {"content_hash": "fcbd743be2e7f64f24ab56e1407a1aeee6758b6b921b7cd02d199126563623ac", "fetched_at": "2026-08-29T13:10:56.831079+00:00", "kind": "homepage", "missing": false, "url": "http://www.nlp.town"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_releases", "no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 3047, "days_push": 778, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 32, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}