{"id":18604401,"url":"https://github.com/samuellucas97/ml-e2e-flask","last_synced_at":"2026-04-16T08:37:29.478Z","repository":{"id":70064694,"uuid":"555575243","full_name":"Samuellucas97/ML-E2E-Flask","owner":"Samuellucas97","description":null,"archived":false,"fork":false,"pushed_at":"2022-10-26T19:12:31.000Z","size":2583,"stargazers_count":0,"open_issues_count":1,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-16T19:09:31.388Z","etag":null,"topics":["flask","machine-learning","random-forest-regression","scikit-learn","seaborn","sqlite3","yellowbrick"],"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/Samuellucas97.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,"zenodo":null}},"created_at":"2022-10-21T21:26:26.000Z","updated_at":"2022-10-26T19:16:05.000Z","dependencies_parsed_at":"2023-02-21T22:00:34.002Z","dependency_job_id":null,"html_url":"https://github.com/Samuellucas97/ML-E2E-Flask","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Samuellucas97/ML-E2E-Flask","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Samuellucas97%2FML-E2E-Flask","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Samuellucas97%2FML-E2E-Flask/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Samuellucas97%2FML-E2E-Flask/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Samuellucas97%2FML-E2E-Flask/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Samuellucas97","download_url":"https://codeload.github.com/Samuellucas97/ML-E2E-Flask/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Samuellucas97%2FML-E2E-Flask/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31878380,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-16T07:36:03.521Z","status":"ssl_error","status_checked_at":"2026-04-16T07:35:53.576Z","response_time":69,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: 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":["flask","machine-learning","random-forest-regression","scikit-learn","seaborn","sqlite3","yellowbrick"],"created_at":"2024-11-07T02:17:44.102Z","updated_at":"2026-04-16T08:37:29.472Z","avatar_url":"https://github.com/Samuellucas97.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Machine Learning project with Flask API\n\nIt contains my ML project involving rental price recommendation based on `area`, `rooms`, `bathroom`, `parking_space`, `floor`, `animal`, `furniture`, `hoa`, and `property tax`. This project was accomplished during [Machine Learning | Solução completa end-to-end (Python)](https://www.udemy.com/course/machine-learning-solucao-completa-end-to-end-api/), an Udemy course. I\n\n\nThe command below clone this repository.\n\n```\n$ git clone https://github.com/Samuellucas97/ML-E2E-Course.git\n$ cd ML-E2E-Course\n```\n\n### Requirements\n\n\n- Python ( version _3.8.10_ )\n\n- Numpy ( version _1.23.4_ )\n    - Use the following command to install: `pip install numpy`\n\n- Pandas ( version _1.5.1_ )\n    - Use the following command to install: `pip install pandas`\n\n- Seaborn ( version _0.12.1_ )\n    - Use the following command to install: `pip install seaborn`\n\n- Sckit-learn ( version _1.1.3_ )\n    - Use the following command to install: `pip install sklearn`\n\n- Yellowbrick (version _1.5_ )\n    - Use the following command to install: `pip install yellowbrick`\n\n- Joblib ( version _1.2.0_ )\n    - Use the following command to install: `pip install joblib`\n\n\n- Flask ( version _2.2.2_ )\n    - Use the following command to install: `pip install flask`\n\n\nYou could check your Sckit-learn lib version, for example, using the following commands on Python interpreter:\n\n```\n\u003e\u003e\u003e import sklearn\n\u003e\u003e\u003e print('The scikit-learn version is {}.'.format(sklearn.__version__))\n```\n\n### How to run\n\nSince you have installed software requirements, you need to execute on the terminal the following command:\n\n```\n$ ./run.sh\n```\n\nA Flask server will be running on [http://127.0.0.1:5000](http://127.0.0.1:5000).\n\nYou can use  the `/api/predictor/` API endpoint to predict rent. We show an example about how to use this in `/test/api.ipynb`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsamuellucas97%2Fml-e2e-flask","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsamuellucas97%2Fml-e2e-flask","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsamuellucas97%2Fml-e2e-flask/lists"}