{"adoption": {"forks": 2365, "observed_at": "2026-08-28T04:09:40.838112+00:00", "stars": 6238}, "canonical_url": "https://ross.abutalabs.com/products/tensorflow_cookbook", "card": {"archived": false, "artifact_type": "learning-resource", "description": "Code for Tensorflow Machine Learning Cookbook", "domain": ["machine-learning", "deep-learning", "tutorials"], "enriched": true, "function": ["machine-learning", "deep-learning", "nlp", "data-science"], "health_score": 20, "homepage": "https://www.packtpub.com/big-data-and-business-intelligence/tensorflow-machine-learning-cookbook-second-edition", "language": "Jupyter Notebook", "license": "MIT", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["nfmcclure/tensorflow_cookbook"], "name": "nfmcclure/tensorflow_cookbook", "platform": ["python"], "pushed_at": "2024-05-23T20:56:53+00:00", "repo": "nfmcclure/tensorflow_cookbook", "stars": 6238, "tags": ["tensorflow", "jupyter-notebooks", "cookbook", "neural-networks", "cnn", "rnn", "svm", "linear-regression", "tensorboard", "packt-book", "natural-language-processing"], "topics": ["tensorflow", "tensorflow-cookbook", "linear-regression", "neural-network", "tensorflow-algorithms", "rnn", "cnn", "svm", "nlp", "packtpub", "machine-learning", "tensorboard", "classification", "regression", "kmeans-clustering", "genetic-algorithm", "ode"], "urls": [], "use_cases": ["learn tensorflow through worked examples", "find code recipes for implementing neural networks in tensorflow", "study cnn and rnn implementations", "learn linear regression and svm in tensorflow", "tensorflow cookbook companion code", "practice machine learning with jupyter notebooks"], "what_it_is": "The official code repository for the book 'TensorFlow Machine Learning Cookbook' by Nick McClure, containing Jupyter Notebook recipes for TensorFlow algorithms. It covers topics from basic tensors through regression, SVMs, neural networks, CNNs, RNNs, and NLP.", "when_to_avoid": ["you need production-ready or maintained TensorFlow code", "you want modern TensorFlow 2.x / Keras idioms", "you need a library rather than educational example code"], "when_to_choose": ["you are reading or studying the TensorFlow Machine Learning Cookbook", "you want notebook-style examples of classic ML algorithms in TensorFlow", "you are learning TensorFlow fundamentals like graphs, variables, and placeholders"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/tensorflow_cookbook", "repo": "nfmcclure/tensorflow_cookbook", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:09:40.838112+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T17:47:11.668009+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "de94cf9288c6c64280be2ae1665c570e040ebf783c17ddecb090d7fe63ef34e9", "fetched_at": "2026-08-28T04:09:40.838112+00:00", "kind": "readme", "missing": false, "url": "https://github.com/nfmcclure/tensorflow_cookbook"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "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": 3736, "days_push": 832, "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}}