{"adoption": {"forks": 365, "observed_at": "2026-08-28T04:05:35.992475+00:00", "stars": 1785}, "canonical_url": "https://ross.abutalabs.com/products/deep_learning_machine_learning_stock", "card": {"archived": false, "artifact_type": "learning-resource", "description": "Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.", "domain": ["fintech", "machine-learning", "data-science"], "enriched": true, "function": ["machine-learning", "deep-learning", "data-science", "trading"], "health_score": 20, "homepage": null, "language": "Jupyter Notebook", "license": "MIT", "license_family": "permissive", "maturity": "active", "member_repos": ["LastAncientOne/Deep_Learning_Machine_Learning_Stock"], "name": "LastAncientOne/Deep_Learning_Machine_Learning_Stock", "platform": ["python", "cross-platform"], "pushed_at": "2024-03-01T00:12:23+00:00", "repo": "LastAncientOne/Deep_Learning_Machine_Learning_Stock", "stars": 1785, "tags": ["stock-prediction", "jupyter-notebooks", "technical-analysis", "feature-engineering", "financial-machine-learning", "educational", "trading"], "topics": ["deep-learning", "machine-learning", "stock-price-prediction", "features-extraction", "financial-engineering", "prediction", "feature-engineering", "feature-extraction", "feature-selection", "stock-data", "stock-trading", "stock-analysis", "stock-prices", "stock-market", "stock-prediction", "algorithms", "data-science", "trading", "technical-analysis", "neural-network"], "urls": [], "use_cases": ["predict stock prices with machine learning", "learn deep learning for stock trading", "feature engineering for financial data", "apply neural networks to stock market data", "study technical analysis with Python", "build stock prediction models in Jupyter notebooks"], "what_it_is": "A collection of Jupyter Notebook tutorials and studies applying machine learning and deep learning algorithms to stock price prediction. It covers feature engineering, technical and fundamental analysis, and both long-term and short-term trading strategies.", "when_to_avoid": ["you need production-ready trading software or a backtesting framework", "you expect guaranteed profitable trading signals", "you need maintained, tested library code rather than study notebooks"], "when_to_choose": ["you want educational notebooks on ML/DL applied to stock prediction", "you are learning feature engineering and selection for financial time series", "you want to experiment with different algorithms on stock data"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/deep_learning_machine_learning_stock", "repo": "LastAncientOne/Deep_Learning_Machine_Learning_Stock", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:05:35.992475+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T03:24:11.476577+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "c1d2cdc5121651b5cb6082738a82856d69f752ad137f3846fa2b1ba571e3dacd", "fetched_at": "2026-08-28T04:05:35.992475+00:00", "kind": "readme", "missing": false, "url": "https://github.com/LastAncientOne/Deep_Learning_Machine_Learning_Stock"}], "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": 2895, "days_push": 916, "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}}