{"id":20156367,"url":"https://github.com/anwarulh007/eduprotect--student-dropout-analysis","last_synced_at":"2026-03-07T03:03:30.925Z","repository":{"id":250981865,"uuid":"773004455","full_name":"Anwarulh007/EduProtect--Student-Dropout-Analysis","owner":"Anwarulh007","description":"EduProtect is a valuable tool for educators, parents, and students in India. By providing accurate predictions and facilitating collaboration, it aims to address the critical issue of student dropouts and ensure a brighter future for all. Used Java in App development and Python for the ML Algorithm in Google Colab.","archived":false,"fork":false,"pushed_at":"2025-05-20T11:54:55.000Z","size":2771,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-04T08:04:49.247Z","etag":null,"topics":["matpoltlib","numpy","python","random-forest-classifier","sckiit-learn"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Anwarulh007.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"License.txt","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":"2024-03-16T13:31:10.000Z","updated_at":"2025-06-30T22:43:31.000Z","dependencies_parsed_at":null,"dependency_job_id":"9a890aa7-3736-49bd-a354-00d1fccf984b","html_url":"https://github.com/Anwarulh007/EduProtect--Student-Dropout-Analysis","commit_stats":null,"previous_names":["anwarulh007/projects","anwarulh007/eduprotect--student-dropout-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Anwarulh007/EduProtect--Student-Dropout-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Anwarulh007%2FEduProtect--Student-Dropout-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Anwarulh007%2FEduProtect--Student-Dropout-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Anwarulh007%2FEduProtect--Student-Dropout-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Anwarulh007%2FEduProtect--Student-Dropout-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Anwarulh007","download_url":"https://codeload.github.com/Anwarulh007/EduProtect--Student-Dropout-Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Anwarulh007%2FEduProtect--Student-Dropout-Analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30206339,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-06T19:07:06.838Z","status":"online","status_checked_at":"2026-03-07T02:00:06.765Z","response_time":53,"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":["matpoltlib","numpy","python","random-forest-classifier","sckiit-learn"],"created_at":"2024-11-13T23:38:34.251Z","updated_at":"2026-03-07T03:03:30.901Z","avatar_url":"https://github.com/Anwarulh007.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n## Eduprotect - Student Dropout Prediction\n\n**Project Overview**\n\nThis project addresses the pressing issue of student dropouts in Indian schools by leveraging machine learning and mobile app development. It provides a comprehensive solution for predicting dropout likelihood and facilitating collaboration between educators, parents, and students.\n\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/EduProtect--Student-Dropout-Analysis/blob/main/Dropout.jpg\" alt=\"Student Dropout Analysis\" style=\"width: auto; height: 320px;\"/\u003e \n\u003c/p\u003e\n\n\n**Key Features**\n\n* Data-Driven Analysis: Employs advanced data analysis techniques to identify key factors influencing dropout rates.\n* Predictive Model: Utilizes a Random Forest classifier, trained on a robust dataset, to accurately predict dropout probability.\n* Mobile App Interface: Offers a user-friendly mobile app built with Android Studio, allowing for easy data input and prediction retrieval.\n* Collaborative Platform: Facilitates collaboration between counselors and skill-based centers to provide timely support to students at risk.\n\n**Dataset Overview**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Dataset%20Overview.jpg\" alt=\"Dataset Overview\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\n**Technologies**\n\n* Programming Languages: Python and Java \n* Machine Learning: Random Forest\n* Development Environments: Google Colab and Android Studio\n* Libraries and Frameworks: Matplotlib, Scikit-learn, Pandas, NumPy,\n\n## How to Use 🚀\n\nTo run the project locally on your machine:\n\n1. **Clone the Repository**:\n   ```bash\n   git clone https://github.com/Anwarulh007/EduProtect--Student-Dropout-Analysis\n2. **Open the Project**:\nNavigate to the project folder and open the index.html file in your web browser to explore the website locally.\n\n\n\n\n**Visualization**\n\nLet's see the distribution of Dropout Rates with respect to School Type using bar chart or pie chart\n\n**School wise Dropout Rates**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Data%20Visualization/Dropout%20Rates%20based%20on%20School%20Type.jpg\" alt=\"School wise Dropout Rates\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\n\nInsights 🔹\n\nThere has been maximum number of dropouts from Government School.\n\n-----------------------------------------------------------------------------------------------------------------------------------\n\n**Location wise Dropout Rates**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Data%20Visualization/Location%20wise%20Dropout%20Rates%20.jpg\" alt=\"Location wise Dropout Rates\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\n\nInsights 🔹\n\nThe greatest percentage of dropouts has come from rural areas.\n\n-----------------------------------------------------------------------------------------------------------------------------------------------\n\n**Gender wise Dropout Rates**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Data%20Visualization/Gender%20wise%20Dropout%20Rates.jpg\" alt=\"Gender wise Dropout Rates\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\nInsights 🔹\n\nThe largest percentage of dropouts have been women.\n\n-----------------------------------------------------------------------------------------------------------------------------------------------\n**Caste wise Dropout Rates**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Data%20Visualization/Caste%20wise%20Dropout%20rates.jpg\" alt=\"Caste wise Dropout Rates\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\nInsights 🔹\n\nThe ST caste has had the highest percentage of dropouts.\n\n-----------------------------------------------------------------------------------------------------------------------------------------------\n**Standard wise Dropout Rates**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Data%20Visualization/Standard%20wise%20Dropout%20Rates.jpg\" alt=\"Standard wise Dropout Rates\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\n Insights🔹\n\nThe highest percentage of dropouts came from the eighth standard.\n\n----------------------------------------------------------------------------------------------------------------------------------------------\n**Age wise Dropout Rates**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Data%20Visualization/Age%20wise%20Dropout%20Rates.jpg\" alt=\"Age wise Dropout Rates\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\n Insights🔹\n\nThe age group of 12 years old accounts for the highest percentage of dropouts.\n\n----------------------------------------------------------------------------------------------------------------------------------------------\n**Overall Dropout Rates based on all Categories**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Data%20Visualization/Overall%20Dropout%20rates%20.jpg\" alt=\"Overall Dropout Rates based on all Categories\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\n Insights🔹\n\nAge/Standard category dropout rates have been the highest. \n\n----------------------------------------------------------------------------------------------------------------------------------------------\n\n **Total Dropout Percentage**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Data%20Visualization/Overall%20Dropout%20Percentage.jpg\" alt=\"Total Dropout Percentage\" style=\"width: auto; height: 300px;\"/\u003e \n\u003c/p\u003e\n\n----------------------------------------------------------------------------------------------------------------------------------------------\n\n**Output**\n\n\u003cp align=\"center\"\u003e \n \u003cimg src=\"https://github.com/Anwarulh007/Student-Dropout-Analysis/blob/main/Output.jpg\" alt=\"Output\" style=\"width: auto; height: 200px;\"/\u003e \n\u003c/p\u003e\n\n**Contributing** 🤝\n\nWe welcome your contributions to enhance the platform and improve user experience! Feel free to open a pull request or issue if you have any suggestions or features to add.\n\n**Contribution Guidelines**:\n\nFork the repository.\nCreate a new branch for your feature or bug fix.\nMake your changes and submit a pull request.\n\n**Usage**\n\n* Login or Create an Account: Users can create an account or login to access the application.\n* Input Student Data: Enter relevant information about the student, such as socio-economic background, academic performance, and other factors.\n* Receive Prediction: The application will use the predictive model to calculate the dropout likelihood and provide a prediction.\n* Access Resources: Counselors and skill-based centers can join the app to access resources, connect with students, and offer support.\n\n**License**\n\nThis project is licensed under the MIT License.\n\n## Made with 🤍 by Anwarul Haque\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanwarulh007%2Feduprotect--student-dropout-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanwarulh007%2Feduprotect--student-dropout-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanwarulh007%2Feduprotect--student-dropout-analysis/lists"}