{"adoption": {"forks": 814, "observed_at": "2026-08-28T04:08:21.988227+00:00", "stars": 3823}, "canonical_url": "https://ross.abutalabs.com/products/dive-into-dl-tensorflow20", "card": {"archived": false, "artifact_type": "learning-resource", "description": "本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现，项目已得到李沐老师的认可", "domain": ["deep-learning", "machine-learning", "tutorials", "computer-vision"], "enriched": true, "function": ["deep-learning", "machine-learning", "nlp", "computer-vision"], "health_score": 20, "homepage": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/", "language": "Jupyter Notebook", "license": "Apache-2.0", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["TrickyGo/Dive-into-DL-TensorFlow2.0"], "name": "TrickyGo/Dive-into-DL-TensorFlow2.0", "platform": ["python", "cross-platform"], "pushed_at": "2023-03-17T08:51:52+00:00", "repo": "TrickyGo/Dive-into-DL-TensorFlow2.0", "stars": 3823, "tags": ["tensorflow2", "jupyter-notebook", "dive-into-deep-learning", "chinese", "textbook", "mxnet-port", "natural-language-processing"], "topics": ["deep-learning", "python3", "dive-into-deep-learning", "tensorflow2", "jupyter-notebook", "nlp", "cv", "tutorials", "chinese-simplified", "book"], "urls": [], "use_cases": ["learn deep learning with tensorflow 2.0", "study dive into deep learning book in chinese", "hands-on deep learning tutorials with jupyter notebooks", "learn neural networks from scratch with code examples", "study nlp and computer vision fundamentals", "convert d2l mxnet examples to tensorflow"], "what_it_is": "A Chinese-language open-source book that ports the 'Dive into Deep Learning' (D2L) textbook's MXNet code examples to TensorFlow 2.0, presented as Jupyter notebooks. It is endorsed by the original author Mu Li and covers deep learning fundamentals through NLP and computer vision.", "when_to_avoid": ["you need PyTorch or MXNet implementations", "you want up-to-date TensorFlow 2.x best practices, as the project is in maintenance mode", "you need production-grade deep learning code rather than educational examples"], "when_to_choose": ["you want to learn deep learning theory alongside runnable TensorFlow 2.0 code", "you prefer Chinese-language instructional material", "you are following the Dive into Deep Learning curriculum but use TensorFlow instead of MXNet"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/dive-into-dl-tensorflow20", "repo": "TrickyGo/Dive-into-DL-TensorFlow2.0", "role": "main", "score": 23}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:08:21.988227+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-29T18:26:23.557624+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "134d2f236d7758c588bb4732c82c0fdc298e236a19203eb0a56c533ebb0c33f3", "fetched_at": "2026-08-29T09:21:14.914102+00:00", "kind": "homepage", "missing": false, "url": "https://trickygo.github.io/Dive-into-DL-TensorFlow2.0/#/"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 0, "longevity": 100, "rhythm": 8}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_readme"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 3054, "days_push": 1265, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 23, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}