{"id":28292969,"url":"https://github.com/shama-llama/data-science-assignments","last_synced_at":"2026-01-25T07:02:16.298Z","repository":{"id":307934620,"uuid":"964060552","full_name":"shama-llama/data-science-assignments","owner":"shama-llama","description":"Repository for CoSc 6262 Course Assignments","archived":false,"fork":false,"pushed_at":"2025-08-03T04:41:57.000Z","size":3866,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-08-03T06:22:54.056Z","etag":null,"topics":["computer-science","cosc-6262","data-science"],"latest_commit_sha":null,"homepage":"","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/shama-llama.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,"zenodo":null}},"created_at":"2025-04-10T16:18:18.000Z","updated_at":"2025-08-03T04:42:00.000Z","dependencies_parsed_at":"2025-08-03T06:35:11.955Z","dependency_job_id":null,"html_url":"https://github.com/shama-llama/data-science-assignments","commit_stats":null,"previous_names":["shama-llama/data-science-assignments"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/shama-llama/data-science-assignments","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shama-llama%2Fdata-science-assignments","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shama-llama%2Fdata-science-assignments/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shama-llama%2Fdata-science-assignments/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shama-llama%2Fdata-science-assignments/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/shama-llama","download_url":"https://codeload.github.com/shama-llama/data-science-assignments/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/shama-llama%2Fdata-science-assignments/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28747308,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-25T05:12:38.112Z","status":"ssl_error","status_checked_at":"2026-01-25T05:04:50.338Z","response_time":113,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["computer-science","cosc-6262","data-science"],"created_at":"2025-05-22T05:11:43.609Z","updated_at":"2026-01-25T07:02:16.286Z","avatar_url":"https://github.com/shama-llama.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Science Assignments\n\n[![Python](https://img.shields.io/badge/Python-3.12+-3776AB?logo=python\u0026logoColor=white)](https://docs.python.org/3.12/)\n[![NumPy](https://img.shields.io/badge/NumPy-2.3.x-4DABCF?logo=numpy\u0026logoColor=white)](https://numpy.org/doc/stable//release/2.3.0-notes.html)\n[![SciPy](https://img.shields.io/badge/SciPy-1.16.x-003786?logo=scipy\u0026logoColor=white)](https://docs.scipy.org/doc/scipy/release/1.16.0-notes.html)\n[![Pandas](https://img.shields.io/badge/Pandas-2.3.x-150458?logo=pandas\u0026logoColor=white)](https://pandas.pydata.org/pandas-docs/version/2.3/index.html)\n[![Scikit-learn](https://img.shields.io/badge/Scikit--learn-1.7+-F7931E?logo=scikit-learn\u0026logoColor=white)](https://scikit-learn.org/stable/whats_new/v1.7.html)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\nThis repository is a collection of assignments that were done as part of the Data Science (CoSc 6262) course. The notebooks cover fundamental topics and practical applications of core Python libraries for data analysis, scientific computing, and machine learning.\n\n## Topics\n\n- **NumPy:** Open source project for numerical computing with Python.\n- **Pandas:** Open source data analysis and manipulation tool.\n- **SciPy:** Tools for array computing and specialized data structures.\n- **scikit-learn:** Tools for predictive data analysis.\n\n## Datasets\n\n\u003e Kaggle, “Titanic - Machine Learning from Disaster,” Kaggle Competitions, 2012. [Online]. Accessed: Apr. 25, 2025. Available: [https://www.kaggle.com/c/titanic/data](https://www.kaggle.com/c/titanic/data).\n\u003e\n\u003e C. Zhang, “IMDB 5000 Movie Dataset,” Kaggle Datasets, [Online]. Accessed: Apr. 25, 2025. Available: [https://www.kaggle.com/datasets/carolzhangdc/imdb-5000-movie-dataset](https://www.kaggle.com/datasets/carolzhangdc/imdb-5000-movie-dataset).\n\n## Project Setup\n\nThis project uses `uv` for package management. `uv` is an extremely fast Python package and project manager, written in Rust that can be used as a drop-in replacement for `pip`, `pip-tools`, `pipx`, `poetry`, `pyenv`, `twine`, `virtualenv`.\n\n- **`uv` Installation**\n\n    ```bash\n    curl -LsSf https://astral.sh/uv/install.sh | sh\n    ```\n\n- **Clone the Repository:**\n\n    ```bash\n    git clone https://github.com/shama-llama/data-science-assignments.git\n    cd data-science-assignments\n    ```\n\n- **Create a Virtual Environment and Install Dependencies with `uv`:**\n\n    ```bash\n    uv venv\n    uv pip install -e .\n    ```\n\n- **Activate the Virtual Environment:**\n\n    ```bash\n    source .venv/bin/activate\n    ```\n\n- **Launch Jupyter Notebook:**\n\n    ```bash\n    jupyter notebook\n    ```\n\n    Navigate to the `notebooks/` directory to run the analysis.\n\n## License\n\nThis project is licensed under the terms of the [MIT](LICENSE) open source license.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshama-llama%2Fdata-science-assignments","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshama-llama%2Fdata-science-assignments","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshama-llama%2Fdata-science-assignments/lists"}