{"id":23173435,"url":"https://github.com/abhinavsharma07/kaggle-comp.","last_synced_at":"2026-02-26T16:18:49.857Z","repository":{"id":266730219,"uuid":"899182779","full_name":"AbhinavSharma07/Kaggle-Comp.","owner":"AbhinavSharma07","description":"A repository showcasing solutions to Kaggle competitions with end-to-end workflows in machine learning and data science.","archived":false,"fork":false,"pushed_at":"2025-04-02T14:20:05.000Z","size":33342,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-02T15:23:35.533Z","etag":null,"topics":["data-preprocessing","datascience","deeplearning","feature-engineering","kaggle","machinelearning","model-evaluation","model-training","predictive-modeling"],"latest_commit_sha":null,"homepage":"https://www.kaggle.com/","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/AbhinavSharma07.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":"2024-12-05T19:17:21.000Z","updated_at":"2025-04-02T14:20:08.000Z","dependencies_parsed_at":"2024-12-22T17:28:00.799Z","dependency_job_id":"b530948b-0112-460a-bc27-dd8b3e42f0aa","html_url":"https://github.com/AbhinavSharma07/Kaggle-Comp.","commit_stats":null,"previous_names":["abhinavsharma07/kaggle-comp."],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhinavSharma07%2FKaggle-Comp.","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhinavSharma07%2FKaggle-Comp./tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhinavSharma07%2FKaggle-Comp./releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AbhinavSharma07%2FKaggle-Comp./manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AbhinavSharma07","download_url":"https://codeload.github.com/AbhinavSharma07/Kaggle-Comp./tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247268096,"owners_count":20911076,"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","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-preprocessing","datascience","deeplearning","feature-engineering","kaggle","machinelearning","model-evaluation","model-training","predictive-modeling"],"created_at":"2024-12-18T05:15:52.598Z","updated_at":"2026-02-26T16:18:49.841Z","avatar_url":"https://github.com/AbhinavSharma07.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🚀 **Kaggle-Comp.**   \n\n \n\n![1634020978101](https://github.com/serkannpolatt/KAGGLE-COMPETITION-NOTEBOOKS/assets/92849974/61495376-53b6-4fdc-82c2-85f4efc46998)\n             \nWelcome to **Kaggle-Comp.**, a dynamic repository showcasing solutions to various **Kaggle competitions**! 🏆  \nYour one-stop guide to exploring:  \n- 💡 **Machine Learning Techniques**  \n- 🛠️ **Data Preprocessing**  \n- 🔍 **Feature Engineering**  \n- 📈 **Model Evaluation**  \n\nDive in to discover **end-to-end workflows** crafted to tackle diverse data science challenges. 🌟  \n\n---\n\n## 📂 **Repository Structure**  \n\nThe repository is neatly organized for seamless navigation. Each competition is housed in its own folder, containing:  \n\n### 📒 **Notebooks**  \n- 📊 **Data Exploration (EDA)**  \n- 🛠️ **Feature Engineering**  \n- 🤖 **Model Training \u0026 Evaluation**  \n\n### ⚙️ **Scripts**  \n- 🔄 **Automation for Data Preprocessing**  \n- 🤝 **Model Training Pipelines**  \n- 📤 **Prediction Generation**  \n\n### 📄 **Submission Files**  \n- ✅ **Final outputs formatted for Kaggle submission**  \n\n### 📝 **Documentation**  \n- 📘 **Readme files or additional notes explaining the approach**  \n\n---\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhinavsharma07%2Fkaggle-comp.","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabhinavsharma07%2Fkaggle-comp.","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabhinavsharma07%2Fkaggle-comp./lists"}