{"id":20504882,"url":"https://github.com/lakshitalearning/churninsight","last_synced_at":"2026-05-09T07:02:32.144Z","repository":{"id":252419845,"uuid":"835135627","full_name":"Lakshitalearning/ChurnInsight","owner":"Lakshitalearning","description":"Customer Churn prediction means knowing which customers are likely to leave or unsubscribe from your service.","archived":false,"fork":false,"pushed_at":"2024-08-09T12:12:00.000Z","size":5641,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-22T23:07:54.516Z","etag":null,"topics":["churn-prediction","data-science","flask","google-colab","machine-learning","predictive-analytics","python","scikit-learn","user-retention","web-development"],"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/Lakshitalearning.png","metadata":{"files":{"readme":"README.txt","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":"2024-07-29T08:27:59.000Z","updated_at":"2024-09-25T14:13:28.000Z","dependencies_parsed_at":"2024-08-09T17:32:14.308Z","dependency_job_id":"224c2142-c223-43f5-b1e8-a06b28f2cce3","html_url":"https://github.com/Lakshitalearning/ChurnInsight","commit_stats":null,"previous_names":["lakshitalearning/churninsight"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Lakshitalearning/ChurnInsight","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lakshitalearning%2FChurnInsight","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lakshitalearning%2FChurnInsight/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lakshitalearning%2FChurnInsight/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lakshitalearning%2FChurnInsight/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Lakshitalearning","download_url":"https://codeload.github.com/Lakshitalearning/ChurnInsight/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lakshitalearning%2FChurnInsight/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32810381,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-08T08:22:46.396Z","status":"online","status_checked_at":"2026-05-09T02:00:06.633Z","response_time":123,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["churn-prediction","data-science","flask","google-colab","machine-learning","predictive-analytics","python","scikit-learn","user-retention","web-development"],"created_at":"2024-11-15T19:41:02.525Z","updated_at":"2026-05-09T07:02:32.127Z","avatar_url":"https://github.com/Lakshitalearning.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\nChurn Prediction App\n\nPredicting user churn with machine learning and web development\n\nOverview\n\nThis repository contains the code for a Churn Prediction App, built as part of my internship at Codsoft. The app uses machine learning algorithms to identify users at risk of leaving a platform, and provides actionable recommendations to reduce churn rates.\n\nFeatures\n\n- User-friendly interface for uploading data and viewing predictions\n- Interactive visualizations for exploring user behavior and churn trends\n- Robust machine learning model for accurate predictions\n- Seamless web development for a smooth user experience\n\nTech Stack\n\n- Python for backend development and data analysis\n- Flask for web application development\n- Scikit-learn for machine learning tasks\n- Pandas, NumPy for data manipulation\n- HTML, CSS, JavaScript for frontend development\n\nUsage\n\n1. Clone the repository and install dependencies\n2. Upload your dataset to the app\n3. View predictions and explore user behavior with interactive visualizations\n4. Use actionable recommendations to reduce churn rates\n\nContributing\n\nContributions are welcome! Please fork the repository and submit a pull request with your changes.\n\nLicense\n\nThis project is licensed under the MIT License. See LICENSE for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flakshitalearning%2Fchurninsight","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flakshitalearning%2Fchurninsight","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flakshitalearning%2Fchurninsight/lists"}