{"id":24696747,"url":"https://github.com/thchilly/mlds102_py_exercises","last_synced_at":"2026-04-06T02:34:54.185Z","repository":{"id":274303812,"uuid":"922506888","full_name":"thchilly/mlds102_py_exercises","owner":"thchilly","description":"Complete exercise sets from MLDS Practical Data Science and Applications course","archived":false,"fork":false,"pushed_at":"2025-01-26T12:18:24.000Z","size":4321,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-01-03T16:26:27.120Z","etag":null,"topics":["data-science","matplotlib","numpy","pandas","python","scikit-learn","scipy","tensorflow"],"latest_commit_sha":null,"homepage":"https://www.eclass.tuc.gr/courses/MLDS103/","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/thchilly.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":"2025-01-26T12:03:26.000Z","updated_at":"2025-01-26T12:18:27.000Z","dependencies_parsed_at":"2025-01-26T13:26:20.784Z","dependency_job_id":"3a14aff9-2d88-411b-bebf-3d1c774c5185","html_url":"https://github.com/thchilly/mlds102_py_exercises","commit_stats":null,"previous_names":["thchilly/mlds102_py_exercises"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/thchilly/mlds102_py_exercises","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thchilly%2Fmlds102_py_exercises","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thchilly%2Fmlds102_py_exercises/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thchilly%2Fmlds102_py_exercises/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thchilly%2Fmlds102_py_exercises/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/thchilly","download_url":"https://codeload.github.com/thchilly/mlds102_py_exercises/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thchilly%2Fmlds102_py_exercises/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31457722,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-05T21:22:52.476Z","status":"online","status_checked_at":"2026-04-06T02:00:07.287Z","response_time":112,"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-science","matplotlib","numpy","pandas","python","scikit-learn","scipy","tensorflow"],"created_at":"2025-01-27T02:03:08.743Z","updated_at":"2026-04-06T02:34:54.170Z","avatar_url":"https://github.com/thchilly.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Practical Data Science and Applications - Python Exercises\n\nThis repository contains Python exercises from the **Practical Data Science and Applications** course, part of the MSc in **Machine Learning and Data Science** program at the Technical University of Crete.\n\n## Course Information\n- **Instructor**: Nikos Giatrakos, Assistant Professor, School of ECE, Technical University of Crete\n- **Topics Covered**:\n  - Python programming for data science\n  - **NumPy**: Numerical computing\n  - **SciPy**: Scientific computing\n  - **Pandas**: Data manipulation and analysis\n  - **Scikit-learn**: Machine learning tools\n  - **TensorFlow**: Deep learning framework\n\n## Structure\nThe repository is organized by topic, with exercises demonstrating practical use cases for each library.\n\n## Notes\nThese exercises were completed as part of coursework and are intended for educational purposes.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthchilly%2Fmlds102_py_exercises","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthchilly%2Fmlds102_py_exercises","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthchilly%2Fmlds102_py_exercises/lists"}