{"id":24956924,"url":"https://github.com/andrewstuart/data-science-from-scratch","last_synced_at":"2025-08-07T16:04:50.182Z","repository":{"id":149489971,"uuid":"41576082","full_name":"andrewstuart/data-science-from-scratch","owner":"andrewstuart","description":"From Joel Grus' book","archived":false,"fork":false,"pushed_at":"2015-08-29T01:21:16.000Z","size":280,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-06-30T23:36:28.898Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"unlicense","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/andrewstuart.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-08-29T01:20:02.000Z","updated_at":"2016-03-20T03:29:55.000Z","dependencies_parsed_at":"2023-04-06T11:23:48.965Z","dependency_job_id":null,"html_url":"https://github.com/andrewstuart/data-science-from-scratch","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/andrewstuart/data-science-from-scratch","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrewstuart%2Fdata-science-from-scratch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrewstuart%2Fdata-science-from-scratch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrewstuart%2Fdata-science-from-scratch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrewstuart%2Fdata-science-from-scratch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/andrewstuart","download_url":"https://codeload.github.com/andrewstuart/data-science-from-scratch/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrewstuart%2Fdata-science-from-scratch/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":269284619,"owners_count":24391127,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-07T02:00:09.698Z","response_time":73,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-02-03T06:41:39.204Z","updated_at":"2025-08-07T16:04:50.073Z","avatar_url":"https://github.com/andrewstuart.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"Data Science from Scratch\n=========================\n\nHere's all the code and examples from my book __[Data Science from Scratch](http://joelgrus.com/2015/04/26/data-science-from-scratch-first-principles-with-python/)__.\n\nEach can be imported as a module, for example (after you cd into the /code directory):\n\n```python\nfrom linear_algebra import distance, vector_mean\nv = [1, 2, 3]\nw = [4, 5, 6]\nprint distance(v, w)\nprint vector_mean([v, w])\n```\n  \nOr can be run from the command line to get a demo of what it does (and to execute the examples from the book):\n\n```bat\npython recommender_systems.py\n```  \n\nAdditionally, I've collected all the [links](https://github.com/joelgrus/data-science-from-scratch/blob/master/links.md) from the book.\n\n## Table of Contents\n\n1. Introduction\n2. A Crash Course in Python\n3. [Visualizing Data](code/visualizing_data.py)\n4. [Linear Algebra](code/linear_algebra.py)\n5. [Statistics](code/statistics.py)\n6. [Probability](code/probability.py)\n7. [Hypothesis and Inference](code/hypothesis_and_inference.py)\n8. [Gradient Descent](code/gradient_descent.py)\n9. [Getting Data](code/getting_data.py)\n10. [Working With Data](code/working_with_data.py)\n11. [Machine Learning](code/machine_learning.py)\n12. [k-Nearest Neighbors](code/nearest_neighbors.py)\n13. [Naive Bayes](code/naive_bayes.py)\n14. [Simple Linear Regression](code/simple_linear_regression.py)\n15. [Multiple Regression](code/multiple_regression.py)\n16. [Logistic Regression](code/logistic_regression.py)\n17. [Decision Trees](code/decision_trees.py)\n18. [Neural Networks](code/neural_networks.py)\n19. [Clustering](code/clustering.py)\n20. [Natural Language Processing](code/natural_language_processing.py)\n21. [Network Analysis](code/network_analysis.py)\n22. [Recommender Systems](code/recommender_systems.py)\n23. [Databases and SQL](code/databases.py)\n24. [MapReduce](code/mapreduce.py)\n25. Go Forth And Do Data Science\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrewstuart%2Fdata-science-from-scratch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandrewstuart%2Fdata-science-from-scratch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrewstuart%2Fdata-science-from-scratch/lists"}