{"id":15159343,"url":"https://github.com/gkar90/grad-admissions-modeling","last_synced_at":"2026-02-06T05:03:05.139Z","repository":{"id":167824704,"uuid":"350185312","full_name":"gkar90/Grad-Admissions-Modeling","owner":"gkar90","description":"Predicted a student's chances of getting into Graduate School based off inputs such as GRE, TOEFL, etc...","archived":false,"fork":false,"pushed_at":"2021-03-30T01:26:05.000Z","size":125,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-18T02:51:00.887Z","etag":null,"topics":["data-science","keras-neural-networks","modeling","python3","tensorflow","tensorflow-models"],"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/gkar90.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}},"created_at":"2021-03-22T02:47:35.000Z","updated_at":"2021-03-30T02:14:46.000Z","dependencies_parsed_at":null,"dependency_job_id":"c95d565b-de75-4c76-94bf-4e95cb0d9c6d","html_url":"https://github.com/gkar90/Grad-Admissions-Modeling","commit_stats":{"total_commits":3,"total_committers":1,"mean_commits":3.0,"dds":0.0,"last_synced_commit":"4fe8980d46a239b7b0b7482993e52bf5422e2dd8"},"previous_names":["gkar90/grad-admissions-modeling"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/gkar90/Grad-Admissions-Modeling","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gkar90%2FGrad-Admissions-Modeling","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gkar90%2FGrad-Admissions-Modeling/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gkar90%2FGrad-Admissions-Modeling/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gkar90%2FGrad-Admissions-Modeling/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/gkar90","download_url":"https://codeload.github.com/gkar90/Grad-Admissions-Modeling/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gkar90%2FGrad-Admissions-Modeling/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29151581,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-06T02:39:25.012Z","status":"ssl_error","status_checked_at":"2026-02-06T02:37:22.784Z","response_time":59,"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":["data-science","keras-neural-networks","modeling","python3","tensorflow","tensorflow-models"],"created_at":"2024-09-26T21:05:01.727Z","updated_at":"2026-02-06T05:03:05.093Z","avatar_url":"https://github.com/gkar90.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Modeling Grad Admissions Data\n\n## Introduction\n\nWith so much emphasis placed on masters degrees these days, it was interesting to me to see if we could come up with a model that could predict your chances of getting into a graduate school by simply inputting your application values.\n\nIn this project, we look at this dataset from Kaggle that provides the parameters considered important during Masters Programs admission applications (such as GRE score, undergrad GPA, TOEFL scores...), and we attempt to take those inputs and create a neural network to predict the chances of that applicant being accepted for the Masters Program.\n\n## Dataset\n\nGraduate Admissions\n\nURL: https://www.kaggle.com/mohansacharya/graduate-admissions?select=Admission_Predict_Ver1.1.csv\n\n\n## Model\n\nWe use a Sequential model with 1 hidden layer, and we use Mean Squared Error for our loss. \n\n## Summary\nOur MSE and MAE were relatively low, telling us our predicted model was not too far off the actual predicted chances of admission.\n\nIt's important to note that the model only had ~500 parameters and very few datapoints. 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