{"adoption": {"forks": 1300, "observed_at": "2026-08-28T04:07:18.045551+00:00", "stars": 2751}, "canonical_url": "https://ross.abutalabs.com/products/paddlepaddle-book", "card": {"archived": true, "artifact_type": "learning-resource", "description": "Deep Learning 101 with PaddlePaddle （『飞桨』深度学习框架入门教程）", "domain": ["deep-learning", "machine-learning", "tutorials", "computer-vision"], "enriched": true, "function": ["deep-learning", "machine-learning", "nlp", "image-processing", "data-visualization"], "health_score": 10, "homepage": "http://www.paddlepaddle.org/documentation/docs/zh/1.2/beginners_guide/quick_start/index.html", "language": "Jupyter Notebook", "license": null, "license_family": "other", "maturity": "maintenance", "member_repos": ["PaddlePaddle/book"], "name": "PaddlePaddle/book", "platform": ["python", "cross-platform"], "pushed_at": "2021-11-12T22:03:47+00:00", "repo": "PaddlePaddle/book", "stars": 2751, "tags": ["jupyter-notebook", "paddlepaddle", "tutorial", "educational", "chinese-documentation", "natural-language-processing", "docker"], "topics": [], "urls": [], "use_cases": ["learn deep learning basics with PaddlePaddle", "run interactive Jupyter notebook tutorials on neural networks", "understand image classification and digit recognition examples", "study NLP tasks like sentiment analysis and machine translation", "get started with the PaddlePaddle framework through hands-on chapters", "learn word2vec and recommender system concepts"], "what_it_is": "An interactive deep learning tutorial book ('Deep Learning 101') built as Jupyter Notebooks using the PaddlePaddle framework. It covers fundamentals like linear regression, digit recognition, image classification, word2vec, recommender systems, sentiment analysis, semantic role labeling, and machine translation, packaged in a Docker image for easy setup.", "when_to_avoid": ["you use TensorFlow, PyTorch, or another framework instead of PaddlePaddle", "you need up-to-date content — the repo has not been updated since late 2021", "you want a production tool or library rather than a learning resource", "you require a maintained project with an explicit license"], "when_to_choose": ["you want a beginner-friendly, hands-on introduction to deep learning using PaddlePaddle", "you prefer runnable Jupyter Notebook chapters with Docker-based setup", "you need bilingual (English/Chinese) deep learning educational material"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/paddlepaddle-book", "repo": "PaddlePaddle/book", "role": "main", "score": 10}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:07:18.045551+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T08:18:55.917220+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "5e144b354d38de7f4f58eca34582db858e2f3737299ec1f4b91e57a40f0846dc", "fetched_at": "2026-08-28T04:07:18.045551+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PaddlePaddle/book"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 35}, "computed_at": "2026-09-03T02:20:16.233290+00:00", "flags": ["no_releases", "archived", "no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 3547, "days_push": 1755, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 10, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}