{"id":29830820,"url":"https://github.com/finite-sample/ds","last_synced_at":"2026-03-18T17:43:37.038Z","repository":{"id":144885653,"uuid":"142067970","full_name":"finite-sample/ds","owner":"finite-sample","description":"Learning From Data","archived":false,"fork":false,"pushed_at":"2022-08-30T19:50:15.000Z","size":36410,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2026-01-11T08:42:31.954Z","etag":null,"topics":["data-science","statistics"],"latest_commit_sha":null,"homepage":null,"language":"HTML","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/finite-sample.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-07-23T20:50:32.000Z","updated_at":"2025-06-19T01:29:59.000Z","dependencies_parsed_at":null,"dependency_job_id":"0a818443-eebb-4269-a8c5-b873193c7925","html_url":"https://github.com/finite-sample/ds","commit_stats":{"total_commits":53,"total_committers":2,"mean_commits":26.5,"dds":"0.018867924528301883","last_synced_commit":"553aa4e6f62a0082f1d104f3af63785775cc75f1"},"previous_names":["finite-sample/ds","soodoku/ds"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/finite-sample/ds","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/finite-sample%2Fds","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/finite-sample%2Fds/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/finite-sample%2Fds/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/finite-sample%2Fds/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/finite-sample","download_url":"https://codeload.github.com/finite-sample/ds/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/finite-sample%2Fds/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29175211,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-06T20:14:21.878Z","status":"ssl_error","status_checked_at":"2026-02-06T20:14:21.443Z","response_time":59,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["data-science","statistics"],"created_at":"2025-07-29T10:11:37.751Z","updated_at":"2026-02-06T20:31:33.060Z","avatar_url":"https://github.com/finite-sample.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Learning From Data\n\n* [Basics of Data Science](01_stat/)\n    - When is the *mean* useful?\n    - Correlation---intuition and problems\n\n* [Cost](02_cost/)\n    - Functional Estimation as Cost Minimization\n    - What's the cost?\n    - How to minimize costs\n    - Derivation of simple linear regression\n\n* [Error, Bias, Variance](03_bias_variance/)\n    - Decomposing Error in Bias, Variance, Irreducible Error\n    - Practical Trade-offs between Bias and Variance\n    - Regularization, Dropout, etc.\n\n* [Evaluating Models](04_eval/)\n    - Metrics for evaluating models\n    - Clearing up confusion about confusion matrices\n    - How to construct your test data\n\n* [What Data to Collect?](05_what_data_to_collect/)\n    - Active learning\n    - Generating types\n\n* [Causal Inference](06_causal_inf/)\n    - *Cosal* Inference\n    - Experimental Inference\n    - Power\n\n* [Fair ML](08_fair_ml/)\n    - Concerns\n    - Solutions\n\n* [Interpretable ML](09_interpretable_ml/)\n    - Why?\n    - How?\n    - Concerns\n\n* [Problem Solving With Data](10_psd/)\n    - Why?\n    - How?\n    - Concerns\n\n* [Model Testing](11_model_testing/)\n    - Why cross-validation isn't enough\n    - Lessons from SWE\n\n### Author\n\nGaurav Sood\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffinite-sample%2Fds","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffinite-sample%2Fds","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffinite-sample%2Fds/lists"}