{"id":18513462,"url":"https://github.com/andryadsm/predicting-house-prices","last_synced_at":"2026-04-04T21:33:20.675Z","repository":{"id":225358803,"uuid":"764848236","full_name":"AndryADSM/Predicting-House-Prices","owner":"AndryADSM","description":"🏘️ Project Predicting House Prices (Python)","archived":false,"fork":false,"pushed_at":"2024-10-15T18:08:48.000Z","size":636,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-14T12:57:03.955Z","etag":null,"topics":["data-analysis","data-preprocessing","data-visualization","feature-engineering","house-prices","machine-learning","matplotlib","numpy","pandas","python","real-estate","seaborn","sklearn"],"latest_commit_sha":null,"homepage":"https://aadsm2355.wixsite.com/andryadsm/predicting-house-prices","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/AndryADSM.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":"2024-02-28T20:24:16.000Z","updated_at":"2024-10-15T18:08:51.000Z","dependencies_parsed_at":"2024-06-22T12:26:27.607Z","dependency_job_id":"fff9eef9-2268-44cf-b135-93537674b338","html_url":"https://github.com/AndryADSM/Predicting-House-Prices","commit_stats":null,"previous_names":["andryadsm/predicting-house-prices"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/AndryADSM/Predicting-House-Prices","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AndryADSM%2FPredicting-House-Prices","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AndryADSM%2FPredicting-House-Prices/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AndryADSM%2FPredicting-House-Prices/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AndryADSM%2FPredicting-House-Prices/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AndryADSM","download_url":"https://codeload.github.com/AndryADSM/Predicting-House-Prices/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AndryADSM%2FPredicting-House-Prices/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31415110,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-04T20:09:54.854Z","status":"ssl_error","status_checked_at":"2026-04-04T20:09:44.350Z","response_time":60,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["data-analysis","data-preprocessing","data-visualization","feature-engineering","house-prices","machine-learning","matplotlib","numpy","pandas","python","real-estate","seaborn","sklearn"],"created_at":"2024-11-06T15:38:32.664Z","updated_at":"2026-04-04T21:33:20.650Z","avatar_url":"https://github.com/AndryADSM.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Predicting House Prices\n\n🌐 Check this project on [my website](https://aadsm2355.wixsite.com/andryadsm/predicting-house-prices)!\n\nGo to [Kaggle](https://www.kaggle.com/code/andrydasilva/house-prices-with-feature-analyzer).\n\n## Files\n- 'house-prices-with-feature-analyzer.ipynb' is the Python Notebook where all the work was done. Works well only inside Kaggle.\n- 'submission.csv' is the final output that is submitted to the Kaggle Competition\n\nYou can also get the code (.ipynb) and output files in Kaggle. Note that they will work well only inside Kaggle.\n\n---\n\n### 📌 Type\nKaggle Competition, Regression.\n\n### ⚜️ Domain\nReal Estate, House Prices.\n​\n### 💻 Technologies\n- Python (Kaggle Notebook)\n    - pandas\n    - numpy\n    - sklearn\n    - matplotlib\n    - seaborn\n\n### 🕹️ Skills\n- Machine Learning\n- Data Preprocessing\n- Feature Engineering\n- Data Visualization\n- Data Analysis\n\n---\n\n🏘️ Worked on the Kaggle competition \"[House Prices - Advanced Regression Techniques](https://www.kaggle.com/competitions/house-prices-advanced-regression-techniques)\" where I successfully predicted the sale price of 1459 houses from a dataset of 1460 records of 79 features using Python 🐍.\n\n🔎 Performed Exploratory Data Analysis (EDA), looking deep for missing values, distributions, counts, correlations and more with a lot of use of pandas, matplotlib and seaborn.\n\n📊 Created a \"Feature Analyzer\", really helpful for EDA, which gives relevant information and plots to quickly get useful insights about a certain feature, categorical or numerical, taking advantage of matplotlib and seaborn.\n\n🧹 Used pandas, numpy and sklearn for cleaning and preprocessing, changing data types, ordinal encoding, dummies, lots of feature engineering 🛠️ and more.\n\n🤖 Tested different models, including several from sklearn, like RandomForestRegressor and GradientBoostingRegressor optimizing with GridSearchCV, concluded with CatBoostRegressor as the best model.\n\n🧾 Evaluated performance with a custom scorer, RMSLE (root-mean-squared-log-error), and got 0.12236, which is as high as top 10% of competitors 🏆.\n\n---\n\n![p1_numr](https://github.com/AndryADSM/Predicting-House-Prices/assets/150280431/62ba6a86-267c-4a04-bc4c-05f78b130255)\n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandryadsm%2Fpredicting-house-prices","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandryadsm%2Fpredicting-house-prices","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandryadsm%2Fpredicting-house-prices/lists"}