{"id":26325199,"url":"https://github.com/kadyb/ogh2023_hack","last_synced_at":"2025-03-15T18:32:11.838Z","repository":{"id":191054976,"uuid":"672253370","full_name":"kadyb/OGH2023_hack","owner":"kadyb","description":"Hackathon \"Automatic land cover mapping\" at OpenGeoHub Summer School 2023","archived":false,"fork":false,"pushed_at":"2023-09-04T20:09:05.000Z","size":22047,"stargazers_count":4,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-06-11T16:07:06.246Z","etag":null,"topics":["classification","hackathon","land-cover","landsat","machine-learning","mapping"],"latest_commit_sha":null,"homepage":"https://kadyb.github.io/OGH2023_hack/","language":"Jupyter Notebook","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/kadyb.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}},"created_at":"2023-07-29T12:47:41.000Z","updated_at":"2023-09-04T20:09:10.000Z","dependencies_parsed_at":"2023-08-27T22:39:28.878Z","dependency_job_id":"9ff11670-071a-40ed-9433-41c5bcfa5334","html_url":"https://github.com/kadyb/OGH2023_hack","commit_stats":{"total_commits":36,"total_committers":2,"mean_commits":18.0,"dds":0.02777777777777779,"last_synced_commit":"f3eeab5a5ccf1afe5a1ac28f2725ea3a32643c13"},"previous_names":["kadyb/ogh2023_hack"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kadyb%2FOGH2023_hack","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kadyb%2FOGH2023_hack/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kadyb%2FOGH2023_hack/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/kadyb%2FOGH2023_hack/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/kadyb","download_url":"https://codeload.github.com/kadyb/OGH2023_hack/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243775142,"owners_count":20346143,"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":["classification","hackathon","land-cover","landsat","machine-learning","mapping"],"created_at":"2025-03-15T18:32:10.247Z","updated_at":"2025-03-15T18:32:11.798Z","avatar_url":"https://github.com/kadyb.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Hackathon \"Automatic land cover mapping\"\n\n\n**The hackathon is finished.\nThe winner is [Maarten Pronk](https://github.com/evetion).\nCongratulations!\nYou can find his notebook in the *solutions* folder.\nThe final ranking is available on Kaggle.**\n\n-----------------------------\n\n[Presentation](https://kadyb.github.io/OGH2023_hack/Presentation.pdf)\n\n[Tutorial](https://kadyb.github.io/OGH2023_hack/Submission.html)\n\n[Tips](https://kadyb.github.io/OGH2023_hack/Tips)\n\n[Rules](https://kadyb.github.io/OGH2023_hack/Rules)\n\n[**Kaggle (registration)**](https://www.kaggle.com/t/87b91a8de46e42f18af5d86073683dc4):\n  * [Dataset](https://www.kaggle.com/competitions/ogh2023/data)\n  * [Submission](https://www.kaggle.com/competitions/ogh2023/submissions)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkadyb%2Fogh2023_hack","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkadyb%2Fogh2023_hack","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkadyb%2Fogh2023_hack/lists"}