{"adoption": {"forks": 617, "observed_at": "2026-08-28T04:07:01.317950+00:00", "stars": 2569}, "canonical_url": "https://ross.abutalabs.com/products/linear-algebra-with-python", "card": {"archived": false, "artifact_type": "learning-resource", "description": "Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.", "domain": ["mathematics", "data-science", "tutorials", "education"], "enriched": true, "function": ["data-visualization", "math"], "health_score": 20, "homepage": null, "language": "Jupyter Notebook", "license": "MIT", "license_family": "permissive", "maturity": "active", "member_repos": ["weijie-chen/Linear-Algebra-With-Python"], "name": "weijie-chen/Linear-Algebra-With-Python", "platform": ["python", "cross-platform"], "pushed_at": "2024-09-05T16:40:42+00:00", "repo": "weijie-chen/Linear-Algebra-With-Python", "stars": 2569, "tags": ["linear-algebra", "jupyter-notebooks", "lecture-notes", "numpy", "sympy", "matplotlib", "matrix-computation", "eigenvalues", "svd", "self-study", "education"], "topics": ["mathematics", "linear-algebra", "python", "jupyter", "data-science", "data-visualization", "data-analysis", "matrix", "matrix-calculations", "computational-science", "eigenvalues", "eigenvectors", "singular-value-decomposition", "multivariate-normal-distribution", "diagonalization", "linear-transformations", "null-space", "gram-schmidt", "symmetric-matrices", "vector-space"], "urls": [], "use_cases": ["learn linear algebra with python", "refresh matrix algebra for data science", "understand eigenvalues and eigenvectors with code examples", "visualize linear transformations and vector spaces", "study SVD and diagonalization with jupyter notebooks", "prepare for econometrics or machine learning math foundations"], "what_it_is": "A collection of Jupyter Notebook lecture notes teaching linear algebra concepts with Python computation and visualization using NumPy, SymPy, and Matplotlib. It targets students and practitioners such as data scientists, quantitative analysts, and econometricians who want to refresh linear algebra foundations for data science and quantitative fields.", "when_to_avoid": ["you need a rigorous proof-based linear algebra course", "you want production-quality or efficient numerical code", "you need a structured course with graded exercises and certification"], "when_to_choose": ["you want intuition and visualization rather than rigorous proofs", "you know basic Python, NumPy, and Matplotlib and want applied linear algebra", "you need a free refresher before studying data science, statistics, or quant finance"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/linear-algebra-with-python", "repo": "weijie-chen/Linear-Algebra-With-Python", "role": "main", "score": 32}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:07:01.317950+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T02:23:20.934482+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "0016dadca5323466bcb8739b9ffb6cb4657b1a02b14740c19a0313ed6e8a2249", "fetched_at": "2026-08-28T04:07:01.317950+00:00", "kind": "readme", "missing": false, "url": "https://github.com/weijie-chen/Linear-Algebra-With-Python"}], "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": 2284, "days_push": 727, "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}}