{"adoption": {"forks": 563, "observed_at": "2026-08-28T04:04:15.184366+00:00", "stars": 1288}, "canonical_url": "https://ross.abutalabs.com/products/deep-reinforcement-learning-hands-on-second-edition", "card": {"archived": false, "artifact_type": "learning-resource", "description": "Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt", "domain": ["reinforcement-learning", "deep-learning", "machine-learning", "tutorials"], "enriched": true, "function": ["reinforcement-learning", "machine-learning", "deep-learning"], "health_score": 20, "homepage": null, "language": "Jupyter Notebook", "license": "MIT", "license_family": "permissive", "maturity": "maintenance", "member_repos": ["PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"], "name": "PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition", "platform": ["python", "cross-platform"], "pushed_at": "2024-04-04T18:46:48+00:00", "repo": "PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition", "stars": 1288, "tags": ["jupyter-notebook", "pytorch", "book-code", "packt", "rl-examples", "gpu"], "topics": [], "urls": [], "use_cases": ["learn deep reinforcement learning from scratch", "example code for DQN and policy gradient methods", "pytorch reinforcement learning tutorials", "study RL algorithms with runnable notebooks", "hands-on practice with gym environments and RL"], "what_it_is": "Companion code repository for the Packt book 'Deep Reinforcement Learning Hands-On, Second Edition', containing Jupyter Notebook examples of deep RL algorithms implemented in PyTorch. It is maintained to keep dependency versions compatible with newer PyTorch releases.", "when_to_avoid": ["you need a production RL library or framework", "you need support for recent Python or PyTorch versions beyond what's tested", "you want a maintained general-purpose RL toolkit"], "when_to_choose": ["you are reading the book and want its code", "you want runnable PyTorch examples of classic deep RL algorithms", "you learn best by experimenting with notebooks"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/deep-reinforcement-learning-hands-on-second-edition", "repo": "PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:04:15.184366+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T04:55:47.622690+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "e40b32c3402ebac9dd986349a49b738398f415f00f9ce6bb01d852195db110fc", "fetched_at": "2026-08-28T04:04:15.184366+00:00", "kind": "readme", "missing": false, "url": "https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On-Second-Edition"}], "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": 2618, "days_push": 881, "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}}