{"id":24397855,"url":"https://github.com/zobayerakib/student-result-data-analysis__data-analysis-project","last_synced_at":"2026-04-07T23:31:25.848Z","repository":{"id":244007636,"uuid":"814036754","full_name":"ZobayerAkib/STudent-Result-Data-Analysis__Data-Analysis-Project","owner":"ZobayerAkib","description":null,"archived":false,"fork":false,"pushed_at":"2024-06-12T08:17:06.000Z","size":586,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-31T15:06:31.812Z","etag":null,"topics":["linear-regression","machine-learning","mathplotlib","numpy","pandas","predictive-analytics","random-forest-regression","seaborn","student-result-analysis"],"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/ZobayerAkib.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-06-12T08:12:33.000Z","updated_at":"2024-06-12T08:19:42.000Z","dependencies_parsed_at":"2024-06-15T01:15:23.411Z","dependency_job_id":null,"html_url":"https://github.com/ZobayerAkib/STudent-Result-Data-Analysis__Data-Analysis-Project","commit_stats":null,"previous_names":["zobayerakib/student-result-data-analysis__data-analysis-project"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ZobayerAkib/STudent-Result-Data-Analysis__Data-Analysis-Project","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZobayerAkib%2FSTudent-Result-Data-Analysis__Data-Analysis-Project","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZobayerAkib%2FSTudent-Result-Data-Analysis__Data-Analysis-Project/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZobayerAkib%2FSTudent-Result-Data-Analysis__Data-Analysis-Project/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZobayerAkib%2FSTudent-Result-Data-Analysis__Data-Analysis-Project/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ZobayerAkib","download_url":"https://codeload.github.com/ZobayerAkib/STudent-Result-Data-Analysis__Data-Analysis-Project/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZobayerAkib%2FSTudent-Result-Data-Analysis__Data-Analysis-Project/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31533823,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-07T16:28:08.000Z","status":"ssl_error","status_checked_at":"2026-04-07T16:28:06.951Z","response_time":105,"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":["linear-regression","machine-learning","mathplotlib","numpy","pandas","predictive-analytics","random-forest-regression","seaborn","student-result-analysis"],"created_at":"2025-01-19T22:49:24.649Z","updated_at":"2026-04-07T23:31:25.832Z","avatar_url":"https://github.com/ZobayerAkib.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Student Result Analysis using Regression Models\n\n### Overview\n\nIn this project, we aimed to analyze student results using machine learning regression models. We divided the dataset into an 80:20 ratio for training and testing purposes. Our goal was to predict the scores of various subjects ('math_score', 'history_score', 'physics_score', 'chemistry_score', 'biology_score', 'english_score', 'geography_score') based on the number of weekly self-study hours.\n\n### Model Training and Evaluation\n\nWe utilized two regression models for training:\n- **Linear Regression (LR)**\n- **Random Forest Regression (RDF)**\n\nAfter training the models, we evaluated their performance using the following metrics:\n- **Mean Absolute Error (MAE)**\n- **Mean Squared Error (MSE)**\n- **Root Mean Squared Error (RMSE)**\n- **R-squared (R²)**\n\n\n### Results\n\n| Model                   | MAE    | MSE     | RMSE    | R²      |\n|-------------------------|--------|---------|---------|---------|\n| Linear Regression (LR)  | 10.5696| 157.1996| 12.5121 | 0.0699  |\n| Random Forest (RDF)    | 10.3420| 155.1183| 12.4352 | 0.0810  |\n\n### Conclusion\n\nBoth models yielded similar results, with the Random Forest Regression slightly outperforming the Linear Regression model. However, the overall predictive performance indicates that the relationship between weekly self-study hours and subject scores may be more complex and may require further investigation or feature engineering.\n\n### Data Source\n\nThe dataset used for this analysis is sourced from [Kaggle].\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzobayerakib%2Fstudent-result-data-analysis__data-analysis-project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzobayerakib%2Fstudent-result-data-analysis__data-analysis-project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzobayerakib%2Fstudent-result-data-analysis__data-analysis-project/lists"}