{"id":16653183,"url":"https://github.com/anuraganalog/grip-tasks","last_synced_at":"2025-10-05T12:14:15.492Z","repository":{"id":112670066,"uuid":"356773633","full_name":"AnuragAnalog/GRIP-Tasks","owner":"AnuragAnalog","description":"Notebooks of the tasks which I have done during the internship","archived":false,"fork":false,"pushed_at":"2021-04-12T01:58:13.000Z","size":14292,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-12T17:17:54.377Z","etag":null,"topics":["april21","data-science","grip","internship","tsf"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AnuragAnalog.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":"2021-04-11T05:18:12.000Z","updated_at":"2021-05-11T07:12:54.000Z","dependencies_parsed_at":"2023-06-10T18:45:18.857Z","dependency_job_id":null,"html_url":"https://github.com/AnuragAnalog/GRIP-Tasks","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/AnuragAnalog/GRIP-Tasks","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnuragAnalog%2FGRIP-Tasks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnuragAnalog%2FGRIP-Tasks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnuragAnalog%2FGRIP-Tasks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnuragAnalog%2FGRIP-Tasks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AnuragAnalog","download_url":"https://codeload.github.com/AnuragAnalog/GRIP-Tasks/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnuragAnalog%2FGRIP-Tasks/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278452682,"owners_count":25989217,"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":"2025-10-05T02:00:06.059Z","response_time":54,"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":["april21","data-science","grip","internship","tsf"],"created_at":"2024-10-12T09:43:27.847Z","updated_at":"2025-10-05T12:14:15.438Z","avatar_url":"https://github.com/AnuragAnalog.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003eGRIP -The Spark Foundation \u003cimg src=\"https://www.thesparksfoundationsingapore.org/images/logo_small.png\" width=\"60\"\u003e\u003c/h1\u003e\n                                                          \n# Task 0 - LinkedIn Profile \n[![Linkedin: Peddi Anurag](https://img.shields.io/badge/LinkedIn-Anurag%20Peddi-black?style=flat\u0026logo=linkedin\u0026labelColor=blue\u0026link=https://www.linkedin.com/in/peddi-anurag-01767a166/)](https://www.linkedin.com/in/peddi-anurag-01767a166/)\n\n# Task 1 - Simple linear regression task\nPredict the percentage of marks that a student is expected to score based upon the number of hours they studied\n\n**Dataset:** http://bit.ly/w-data\n\n**Notebook:** https://github.com/AnuragAnalog/GRIP-Tasks/blob/main/task1/GRIP%20TASK1.ipynb\n\n\u003e Predicted marks for 9.25 hours is 94.75272937202871\n\n# Task 2 - To Explore Unsupervised Machine Learning\nFrom the given ‘Iris’ dataset, predict the optimum number of clusters and represent it visually.\n\n**Dataset:** https://drive.google.com/file/d/11Iq7YvbWZbt8VXjfm06brx66b10YiwK-/view?usp=sharing\n\n**Notebook:** https://github.com/AnuragAnalog/GRIP-Tasks/blob/main/task2/GRIP%20Task2.ipynb\n \n# Task 6 - To Explore Decision Tree Algorithm.For the given ‘Iris’ dataset\ncreate the Decision Tree classifier and visualize it graphically. The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.\n\n**Dataset:** https://drive.google.com/file/d/11Iq7YvbWZbt8VXjfm06brx66b10YiwK-/view?usp=sharing\n\n**Notebook:** https://github.com/AnuragAnalog/GRIP-Tasks/blob/main/task6/GRIP%20Task6.ipynb\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanuraganalog%2Fgrip-tasks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanuraganalog%2Fgrip-tasks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanuraganalog%2Fgrip-tasks/lists"}