{"id":30848315,"url":"https://github.com/sunita10sonar/admissionpredict_ann","last_synced_at":"2026-05-19T07:37:40.301Z","repository":{"id":312702777,"uuid":"1048417027","full_name":"Sunita10Sonar/AdmissionPredict_ANN","owner":"Sunita10Sonar","description":"Artificial Neural Network regression model to predict graduate admission chances based on academic profiles.","archived":false,"fork":false,"pushed_at":"2025-09-01T12:18:30.000Z","size":37,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-09-01T14:25:07.265Z","etag":null,"topics":["deep-learning","machine-learning","neural-network","regression","tensorflow"],"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/Sunita10Sonar.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,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-09-01T12:12:23.000Z","updated_at":"2025-09-01T12:22:16.000Z","dependencies_parsed_at":"2025-09-01T14:25:55.438Z","dependency_job_id":"23ec8b4e-592e-4b82-8bb1-6f1d7c993d82","html_url":"https://github.com/Sunita10Sonar/AdmissionPredict_ANN","commit_stats":null,"previous_names":["sunita10sonar/admissionpredict_ann"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/Sunita10Sonar/AdmissionPredict_ANN","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sunita10Sonar%2FAdmissionPredict_ANN","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sunita10Sonar%2FAdmissionPredict_ANN/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sunita10Sonar%2FAdmissionPredict_ANN/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sunita10Sonar%2FAdmissionPredict_ANN/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Sunita10Sonar","download_url":"https://codeload.github.com/Sunita10Sonar/AdmissionPredict_ANN/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Sunita10Sonar%2FAdmissionPredict_ANN/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273990205,"owners_count":25203290,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-09-07T02:00:09.463Z","response_time":67,"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":["deep-learning","machine-learning","neural-network","regression","tensorflow"],"created_at":"2025-09-07T03:08:21.225Z","updated_at":"2026-05-19T07:37:40.268Z","avatar_url":"https://github.com/Sunita10Sonar.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🎓 Admission Prediction using ANN (Regression Model)\n\n## ⭐ Situation\nGraduate school admission is highly competitive, and students often want to estimate their **chance of admission** before applying.  \nTraditional statistical methods can struggle to capture the nonlinear relationships between factors such as GRE, TOEFL, CGPA, university rating, SOP, LOR, and research experience.\n\n---\n\n## 🎯 Task\nThe objective of this project is to **predict the probability of admission** based on a student’s profile by:  \n- Preprocessing academic data.  \n- Building and training an **Artificial Neural Network (ANN)** regression model.  \n- Evaluating prediction accuracy with proper metrics.  \n\n---\n\n## 🔧 Action\nSteps taken to achieve the task:  \n1. **Data Exploration \u0026 Preprocessing**  \n   - Cleaned and normalized the dataset.  \n   - Performed exploratory data analysis (EDA) to understand correlations.  \n\n2. **Feature Engineering**  \n   - Selected key features (GRE, TOEFL, CGPA, etc.).  \n   - Split the dataset into training and test sets.  \n\n3. **Model Development**  \n   - Built an ANN regression model using **TensorFlow/Keras**.  \n   - Tuned hyperparameters (hidden layers, activation functions, optimizer).  \n\n4. **Model Evaluation**  \n   - Assessed accuracy using **Mean Squared Error (MSE)** and **R² score**.  \n   - Visualized actual vs. predicted admission probabilities.  \n\n---\n\n## 📊 Result\n- Successfully built an ANN regression model to predict **chance of admission** (0–1 scale).  \n- Found that **CGPA, GRE, and Research experience** are the most influential factors.  \n- Model provides a data-driven way for students to **assess admission likelihood** before applying.  \n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsunita10sonar%2Fadmissionpredict_ann","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsunita10sonar%2Fadmissionpredict_ann","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsunita10sonar%2Fadmissionpredict_ann/lists"}