{"id":26129871,"url":"https://github.com/theovidal/hickathon","last_synced_at":"2025-07-08T15:03:41.570Z","repository":{"id":279948631,"uuid":"896213881","full_name":"theovidal/hickathon","owner":"theovidal","description":"💧 Hackathon: Using ML to predict water shortages during summer","archived":false,"fork":false,"pushed_at":"2025-02-28T11:06:21.000Z","size":23097,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-10T19:59:54.602Z","etag":null,"topics":["hackathon","machine-learning","water-resources"],"latest_commit_sha":null,"homepage":"","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/theovidal.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":"2024-11-29T19:42:52.000Z","updated_at":"2025-02-28T11:06:52.000Z","dependencies_parsed_at":null,"dependency_job_id":"8fc745b6-2e01-4074-9b41-de6ffbe820a7","html_url":"https://github.com/theovidal/hickathon","commit_stats":null,"previous_names":["theovidal/hickathon"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/theovidal/hickathon","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theovidal%2Fhickathon","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theovidal%2Fhickathon/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theovidal%2Fhickathon/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theovidal%2Fhickathon/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/theovidal","download_url":"https://codeload.github.com/theovidal/hickathon/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theovidal%2Fhickathon/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264292908,"owners_count":23586059,"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":["hackathon","machine-learning","water-resources"],"created_at":"2025-03-10T19:59:36.836Z","updated_at":"2025-07-08T15:03:41.540Z","avatar_url":"https://github.com/theovidal.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n    \u003cimg src=\"assets/waterai.png\" alt=\"water.ai logo\" width=\"300px\"\u003e\n    \u003ch1\u003eSubmission repository for Hi!ckathon 5\u003c/h1\u003e\n    \u003ch3\u003e💧 Using ML to predict water shortages during summer 🚱\u003c/h3\u003e\n    \u003cimg src=\"assets/hiparis.jpg\" alt=\"Hi! Paris Logo\" width=\"250px\"\u003e\n\u003c/div\u003e\n\n# Original subject\n\nThis subject was proposed by Hi! Paris for this edition of the Hi!ckathon:\n\n_\"The goal is to build an AI model that can **predict the watertable/ground water** levels of french piezometric stations, with a focus on the **summer** months. To build this model, you were given piezometric/watertable, weather, hydrology, water withdrawal and economic data._\n\n_But beyond producing an AI model, the competition will ask you to **realistically project your solution in a market** / real-world context.\"_\n\n# Our deliverables\n\nWe worked in a team of six in 48 hours to bring a solution for this problem, using a technical approach (Machine Learning model) as well as a business approach (a product to sell in a market).\n\n## Machine Learning program\n\nThe notebooks in the repository are my (Théo Vidal) personal codes for the project, as the methodology in our team was to experiment various approaches for the problem and share them with the others for their own research. \n\n- [Hickathon.ipynb](./Hickathon.ipynb): all data cleaning, visualization, processing pipeline with model training (XGBoost with hyperparameters search)\n- [Hickathon submission.ipynb](./Hickathon%20submission.ipynb): notebook for inference based on trained weights\n\nYou can also find an [HTML visualization tool](./docs/visualization.html) to preview data on a map and see the evolution in time.\n\n## Business report\n\nAlso available in [PDF format](./docs/water.ai%20-%20Scientific\u0026Business%20approach.pdf)\n\n![Page 1](./docs/water.ai%20-%20Scientific\u0026Business%20approach-1.png)\n![Page 2](./docs/water.ai%20-%20Scientific\u0026Business%20approach-2.png)\n![Page 3](./docs/water.ai%20-%20Scientific\u0026Business%20approach-3.png)\n![Page 4](./docs/water.ai%20-%20Scientific\u0026Business%20approach-4.png)\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftheovidal%2Fhickathon","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftheovidal%2Fhickathon","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftheovidal%2Fhickathon/lists"}