{"id":18625611,"url":"https://github.com/mdbecker/pydata_2013","last_synced_at":"2025-07-28T14:32:32.509Z","repository":{"id":141939231,"uuid":"11748255","full_name":"mdbecker/pydata_2013","owner":"mdbecker","description":"PyData Boston 2013 talks: \"Intro to scikit-learn\" \u0026 \"Realtime Predictive Analytics: Using scikit-learn and RabbitMQ\"","archived":false,"fork":false,"pushed_at":"2014-01-05T02:46:53.000Z","size":46972,"stargazers_count":11,"open_issues_count":0,"forks_count":3,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-05-13T14:35:35.474Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mdbecker.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":"2013-07-29T19:47:41.000Z","updated_at":"2022-04-03T21:40:47.000Z","dependencies_parsed_at":"2023-03-13T10:27:30.882Z","dependency_job_id":null,"html_url":"https://github.com/mdbecker/pydata_2013","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mdbecker/pydata_2013","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mdbecker%2Fpydata_2013","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mdbecker%2Fpydata_2013/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mdbecker%2Fpydata_2013/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mdbecker%2Fpydata_2013/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mdbecker","download_url":"https://codeload.github.com/mdbecker/pydata_2013/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mdbecker%2Fpydata_2013/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":267530309,"owners_count":24102542,"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":"2025-07-28T02:00:09.689Z","response_time":68,"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":"2024-11-07T04:35:23.003Z","updated_at":"2025-07-28T14:32:32.428Z","avatar_url":"https://github.com/mdbecker.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"pydata_2013\n===========\n\nPyData Boston 2013 talks: \"Intro to scikit-learn\" \u0026amp; \"Realtime Predictive Analytics: Using scikit-learn and RabbitMQ\"\n\nIf you are interested in working for [the best company](https://www.aweber.com/blog/press/aweber-wins-2013-best-places-to-work-by-philadelphia-business-journal) in the universe, [send me an email](mailto:mike@beckerfuffle.com).\n![The best company in the universe](/AWeber_Universe.jpg \"The best company in the universe\")\n\nIntro to scikit-learn\n---------------------\nIn this talk you will get a brief overview of Machine Learning and scikit-learn. This is a repeat of the talk I gave for PhillyPUG \u0026 DataPhilly which is a scaled down version of this talk from Pycon 2013 http://github.com/jakevdp/sklearn_pycon2013.\n\n[![ScreenShot](http://i.imgur.com/7fFKU1G.png)](http://vimeo.com/72859487)\n\n[SlideShare](http://www.slideshare.net/aweberinc/intro-to-scikit-learn-pydata-boston-2013)\n\nRealtime Predictive Analytics: Using scikit-learn and RabbitMQ\n--------------------------------------------------------------\nIn this talk I'll describe how to deploy a predictive model in a production environment using RabbitMQ and scikit-learn. I'll show a realtime content classification system to demonstrate this design.\n\n[![ScreenShot](http://i.imgur.com/7mNdaaj.png)](http://vimeo.com/73628112)\n\n[SlideShare](http://www.slideshare.net/aweberinc/realtime-predictive-analytics-pydata-boston-2013)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmdbecker%2Fpydata_2013","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmdbecker%2Fpydata_2013","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmdbecker%2Fpydata_2013/lists"}