{"id":16828514,"url":"https://github.com/jameslamb/talks","last_synced_at":"2025-09-06T13:32:47.264Z","repository":{"id":43214698,"uuid":"182484984","full_name":"jameslamb/talks","owner":"jameslamb","description":"Conference talks, meetup talks, and misc. writing","archived":false,"fork":false,"pushed_at":"2024-03-07T05:01:55.000Z","size":14234,"stargazers_count":24,"open_issues_count":0,"forks_count":2,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-12-24T02:25:39.673Z","etag":null,"topics":["conference-talk","data-science","machine-learning","open-source","presentations","python","r"],"latest_commit_sha":null,"homepage":"","language":"CSS","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jameslamb.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-04-21T03:25:04.000Z","updated_at":"2024-12-12T20:29:53.000Z","dependencies_parsed_at":"2024-10-28T12:45:57.540Z","dependency_job_id":null,"html_url":"https://github.com/jameslamb/talks","commit_stats":{"total_commits":75,"total_committers":2,"mean_commits":37.5,"dds":"0.013333333333333308","last_synced_commit":"92340a9c4f4f7a2552f37be91322bb49242664d5"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jameslamb%2Ftalks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jameslamb%2Ftalks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jameslamb%2Ftalks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jameslamb%2Ftalks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jameslamb","download_url":"https://codeload.github.com/jameslamb/talks/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":232126168,"owners_count":18476190,"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","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":["conference-talk","data-science","machine-learning","open-source","presentations","python","r"],"created_at":"2024-10-13T11:27:01.522Z","updated_at":"2025-09-06T13:32:47.117Z","avatar_url":"https://github.com/jameslamb.png","language":"CSS","funding_links":[],"categories":[],"sub_categories":[],"readme":"# talks\n\nThis repository holds information on talks I've given at conferences and meetups.\n\nIf you attended one of these talks and have follow-up questions\n\n1. Thank you so much for attending!\n2. Open [an issue](https://github.com/jameslamb/talks/issues) or message me at the contact information at https://github.com/jameslamb\n\n## Gallery\n\n### Conferences and Meetups\n\nClick the \"title\" links below for links to slides, code, and other background information.\n\n| title                                                                                     |                                video(s)                                |\n|:------------------------------------------------------------------------------------------|:----------------------------------------------------------------------:|\n| [\"Comparing `{lightgbm}` to other R GBDT libraries\"][26]                                  |                 [New York Stats Meetup (May 2021)][27]                 |\n| [\"Dask and LightGBM (light intro)\"][34]                                                   |               [Austin Python Meetup (Nov 2021)][35]               |\n| [\"Does that CSV belong on PyPI? Probably not\"][40]                                        |                             [SciPy 2022][41]                           |\n| [\"Economics Consulting\"][14]                                                              |                                  ---                                   |\n| [\"Economics as a Science\"][13]                                                            |                                  ---                                   |\n| [\"Economists Should Learn Data Science\"][18]                                              |                                  ---                                   |\n| [\"Every Way SpotHero Uses Python\"][38]                                                    |               [ChiPy `__main__` meeting (Mar 2022)][39]                |\n| [\"How Distributed LightGBM on Dask Works\"][29]                                            |                [Dask Distributed Summit (May 2021)][30]                |\n| [\"Intro to Cloud Computing\"][15]                                                          |                 [iRisk Lab Hack Night (Apr 2020)][16]                  |\n| [\"LightGBM's Road to CRAN\"][7]                                                            |                    [satRdays Chicago (Apr 2020)][8]                    |\n| [\"People Shape Software\"][9]                                                              |                   [satRdays Chicago (Apr 2019)][10]                    |\n| [\"Prefect in 5 Minutes\"][28]                                                              |                    [ChiPy Data SIG (May 2021)][31]                     |\n| [\"Proliferation of New Database Technologies \u003cbr\u003eand Implications for Data Science\"][11]  |              [Domino Data Science Pop-Up (Oct 2017)][12]               |\n| [\"R From the Command Line\"][23]                                                           |                      [LA R Users (Mar 2021)][24]                       |\n| [\"Recent Developments in LightGBM\"][19]                                                   |                [LA Data Science Meetup (Jan 2021)][20]                 |\n| [\"Road to a Data Science Career\"][3]                                                      |                  [iRisk Lab Hack Night (Aug 2020)][4]                  |\n| [\"Scaling LightGBM with Python and Dask\"][5]                                              |    [PyData Montreal (Jan 2021)][21]\u003cbr\u003e[Chicago ML (Jan 2021)][22]     |\n| [\"Scaling Machine Learning with Python and Dask\"][5]                                      | [Chicago Cloud Conference (Sep 2020)][6]\u003cbr\u003e[ODSC East (Apr 2021)][25] |\n| [\"Those tables were empty!\"][47]                                                             | ---  |\n| [\"Using Retry Logic in R HTTP Clients\"][17]                                               |                                  ---                                   |\n| [\"You can do Open Source\"][1]                                                             |                    [satRdays Chicago (Apr 2019)][2]                    |\n| [\"You can and should do Open Source\"][32]                                                 |                     [CatBoost: от 0 до 1.0.0][33]                      |\n\n### Podcasts\n\n* [\"Building for Small Data Science Teams\"][36] ([MLOps Community podcast (Dec 2021)][37])\n* [\"From Open Source to Traditional ML\"][42] ([Top End Devs (Dec 2023)][43])\n\n### Writing\n\n* \"Scaling LightGBM with Dask\" ([ODSC Blog (Feb 2021)][44])\n* \"What does a Machine Learning Engineer Do?\" ([MLOps Community Blog (Sep 2022)][45])\n* \"Once A Maintainer: James Lamb\" ([Allison Pike's \"Once a Maintainer\" Blog (Oct 2023)][46])\n\n[1]: ./you-can-do-open-source\n[2]: https://www.youtube.com/watch?v=quFhQvizBE8\u0026t=4h35m15s\n[3]: ./road-to-a-data-science-career\n[4]: https://www.youtube.com/watch?v=-WCa_MjJZ9I\n[5]: ./dask-machine-learning\n[6]: https://www.youtube.com/watch?v=qglSZktDz40\u0026t=1800s\n[7]: ./lightgbm-road-to-cran\n[8]: https://www.youtube.com/watch?v=xA7l7N2ktFk\u0026feature=youtu.be\u0026t=6236\n[9]: ./people-shape-software\n[10]: https://www.youtube.com/watch?v=quFhQvizBE8\u0026t=2h24m30s\n[11]: ./proliferation-of-new-database-technologies\n[12]: https://dominodatalab.wistia.com/medias/0z04na8njm\n[13]: ./economics-as-a-science\n[14]: ./economic-consulting\n[15]: ./cloud-intro\n[16]: https://www.youtube.com/watch?v=495GqB_xcqE\n[17]: ./chi-r-collab-httr\n[18]: ./econ-learn-data-science\n[19]: ./recent-developments-in-lightgbm\n[20]: https://www.youtube.com/watch?list=PLVwJeG_Q73i7UpMciUK7ckTD8zQc7oT0W\u0026v=5nKSMXBFhes\u0026feature=emb_title\n[21]: https://www.youtube.com/watch?v=vajaT1FNP6I\n[22]: https://www.youtube.com/watch?v=hK4fiXz8zXM\n[23]: ./r-from-the-command-line\n[24]: https://www.youtube.com/watch?v=5kmUE-qHziA\n[25]: https://www.youtube.com/watch?v=8kKVrJC7op4\n[26]: ./comparing-lightgbm-to-other-r-gbdt-libraries\n[27]: https://www.youtube.com/watch?v=z64JFJQR_J0\n[28]: ./prefect-in-5-minutes\n[29]: ./how-distributed-lightgbm-on-dask-works\n[30]: https://zoom.us/rec/share/2MDNheUjidMT7EOcVuD0qnCph3OGnk9Wjf6QZo-8YLO95bzCEHaiDH6I5LmeqXE.Y87S6St0o2DuG29G\n[31]: https://www.youtube.com/watch?v=z7v40C99wO4\u0026t=3415s\n[32]: ./you-can-and-should-do-open-source\n[33]: https://www.youtube.com/watch?v=ObzrXjqWcTY\u0026t=9200s\n[34]: ./dask-lightgbm-short-talk\n[35]: https://www.youtube.com/watch?v=Yh-jK497VZU\n[36]: ./building-for-small-data-science-teams\n[37]: https://www.youtube.com/watch?v=yAsPfhI5Jd8\n[38]: ./every-way-spothero-uses-python\n[39]: https://www.youtube.com/watch?v=d5iZONHGQT0\u0026t=38m34s\n[40]: ./does-that-csv-belong-on-pypi\n[41]: https://www.youtube.com/watch?v=-Jqx5QxaNmA\u0026list=PLYx7XA2nY5GcuVaU-l1hPOFgtnhmcHZzC\u0026index=10\u0026t=3h24m50s\n[42]: ./from-open-source-to-traditional-ml\n[43]: https://topenddevs.com/podcasts/adventures-in-machine-learning/episodes/from-open-source-to-traditional-ml-with-james-lamb-ml-138\n[44]: https://opendatascience.com/scaling-lightgbm-with-dask/\n[45]: https://mlops.community/james-lamb-machine-learning-engineer/\n[46]: https://onceamaintainer.substack.com/p/once-a-maintainer-james-lamb\n[47]: ./those-tables-were-empty\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjameslamb%2Ftalks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjameslamb%2Ftalks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjameslamb%2Ftalks/lists"}