{"id":26243530,"url":"https://github.com/diem0n/100daysofdatascience","last_synced_at":"2026-04-09T20:49:38.985Z","repository":{"id":246051806,"uuid":"819952082","full_name":"Diem0n/100daysofdatascience","owner":"Diem0n","description":"This repository is a collection of things i do on as a data scientist each day as i am hired at a fictional company called keko corp","archived":false,"fork":false,"pushed_at":"2024-07-06T18:30:48.000Z","size":2357,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-13T10:35:38.888Z","etag":null,"topics":["data-analysis","data-engineering","data-science","data-science-from-scratch","data-warehousing","machine-learning","python"],"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/Diem0n.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}},"created_at":"2024-06-25T13:58:35.000Z","updated_at":"2024-07-06T18:30:52.000Z","dependencies_parsed_at":"2024-07-06T19:41:21.791Z","dependency_job_id":"c6654951-8b66-41a1-8046-77d3495c1825","html_url":"https://github.com/Diem0n/100daysofdatascience","commit_stats":null,"previous_names":["diem0n/100daysofdatascience"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Diem0n/100daysofdatascience","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Diem0n%2F100daysofdatascience","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Diem0n%2F100daysofdatascience/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Diem0n%2F100daysofdatascience/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Diem0n%2F100daysofdatascience/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Diem0n","download_url":"https://codeload.github.com/Diem0n/100daysofdatascience/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Diem0n%2F100daysofdatascience/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28061264,"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":"2025-12-26T02:00:06.189Z","response_time":55,"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":["data-analysis","data-engineering","data-science","data-science-from-scratch","data-warehousing","machine-learning","python"],"created_at":"2025-03-13T10:28:37.154Z","updated_at":"2025-12-26T21:18:31.732Z","avatar_url":"https://github.com/Diem0n.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 100 Days of Data Science\n\nThis repository is a collection of my daily learnings and activities as I embark on a journey to become a data scientist from scratch. I have been \"hired\" by a fictional company called Keko Corp, where I will be diving into various aspects of data science, data engineering, data analytics, and data warehousing.\n\n## Repository Structure\n\nEach day is documented with detailed explanations, code snippets, and examples. The topics covered range from basic Python programming to advanced data visualization,data engineering, data warehousing, machine learning, deep learning and linear algebra concepts.\n\n\n## How to Use This Repository\n\nEach day's work is documented in a separate markdown file within this repository. 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