{"id":17494613,"url":"https://github.com/bsenst/housing-germany","last_synced_at":"2026-05-09T10:37:46.842Z","repository":{"id":203451900,"uuid":"709636869","full_name":"bsenst/housing-germany","owner":"bsenst","description":"Machine learning project based on the Kaggle \"Apartment rental offers in Germany\" dataset for the Data Talks Club Machine Learning Zoomcamp 2023.","archived":false,"fork":false,"pushed_at":"2023-10-29T12:24:19.000Z","size":147,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-02T18:45:08.973Z","etag":null,"topics":["datatalksclub","flask","germany","housing-prices","midterm-project","streamlit","zoomcamp"],"latest_commit_sha":null,"homepage":"https://housing-germany.streamlit.app/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bsenst.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}},"created_at":"2023-10-25T05:07:00.000Z","updated_at":"2023-10-29T11:02:16.000Z","dependencies_parsed_at":null,"dependency_job_id":"a71357b9-eb45-4c4a-b1d9-1ef91c498768","html_url":"https://github.com/bsenst/housing-germany","commit_stats":{"total_commits":21,"total_committers":1,"mean_commits":21.0,"dds":0.0,"last_synced_commit":"be8256f277eecbe1059883f961cb99e8a4840b65"},"previous_names":["bsenst/housing-germany"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bsenst%2Fhousing-germany","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bsenst%2Fhousing-germany/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bsenst%2Fhousing-germany/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bsenst%2Fhousing-germany/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bsenst","download_url":"https://codeload.github.com/bsenst/housing-germany/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246076935,"owners_count":20719894,"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":["datatalksclub","flask","germany","housing-prices","midterm-project","streamlit","zoomcamp"],"created_at":"2024-10-19T13:28:41.345Z","updated_at":"2026-05-09T10:37:41.810Z","avatar_url":"https://github.com/bsenst.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# housing-germany\nMachine learning project for the [Data Talks Club Machine Learning Zoomcamp](https://github.com/DataTalksClub/machine-learning-zoomcamp) 2023.\n\n# Problem Description\nThe real estate market in Germany is dynamic and influenced by various factors such as location, property type, size, amenities, and economic conditions. Accurately predicting rental prices is crucial for both property owners and potential tenants to make informed decisions. In this context, developing a reliable machine learning model to predict housing rent prices in Germany becomes paramount.\n\nThe objective of this project is to build a predictive model that can estimate the monthly rent for residential properties in Germany based on selected features.\n# Instructions\n\n## Dependency Management\n\n```\npip install -r requirements.txt\n```\n\n## Dataset\n\u003e CorrieBar. (2019, October). Apartment rental offers in Germany, Version 6. Retrieved October 28, 2023 from https://www.kaggle.com/datasets/corrieaar/apartment-rental-offers-in-germany\n\nTo download the dataset follow the instructions on https://www.kaggle.com/docs/api\n\n```\nkaggle datasets download -d corrieaar/apartment-rental-offers-in-germany\nunzip apartment-rental-offers-in-germany.zip\n```\n\n## Explore Data (EDA) \u0026 Train Optimized Model with Notebook\n\nOpen the `housing-eda.ipynb` notebook.\n\n## Run Model Training Script\n\n```\npython scripts/train.py\n```\n\n## Test Model Prediction Script\n\n```\npython scripts/predict.py\n```\n\n# Model Deployment\n\n## Run App\n\n```\npython flask app/flask_app.py\n```\n\n```\nstreamlit run app/streamlit_app.py\n```\n\n## Run Containerized App with Docker \n\n```\ndocker build -t model_server .\ndocker run -p 5000:5000 -p 8501:8501 model_server\n```\n\n## Streamlit Cloud Deployed\n\nVisit the live app at [housing-germany.streamlit.app](https://www.streamlit.io)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbsenst%2Fhousing-germany","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbsenst%2Fhousing-germany","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbsenst%2Fhousing-germany/lists"}