https://github.com/shama-llama/data-science-assignments

Repository for CoSc 6262 Course Assignments
https://github.com/shama-llama/data-science-assignments

computer-science cosc-6262 data-science

Last synced: 5 months ago
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Repository for CoSc 6262 Course Assignments

• Host: GitHub
• URL: https://github.com/shama-llama/data-science-assignments
• Owner: shama-llama
• License: mit
• Created: 2025-04-10T16:18:18.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-08-03T04:41:57.000Z (11 months ago)
• Last Synced: 2025-08-03T06:22:54.056Z (11 months ago)
• Topics: computer-science, cosc-6262, data-science
• Language: Jupyter Notebook
• Homepage:
• Size: 3.69 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Data Science Assignments

[![Python](https://img.shields.io/badge/Python-3.12+-3776AB?logo=python&logoColor=white)](https://docs.python.org/3.12/)

[![NumPy](https://img.shields.io/badge/NumPy-2.3.x-4DABCF?logo=numpy&logoColor=white)](https://numpy.org/doc/stable//release/2.3.0-notes.html)

[![SciPy](https://img.shields.io/badge/SciPy-1.16.x-003786?logo=scipy&logoColor=white)](https://docs.scipy.org/doc/scipy/release/1.16.0-notes.html)

[![Pandas](https://img.shields.io/badge/Pandas-2.3.x-150458?logo=pandas&logoColor=white)](https://pandas.pydata.org/pandas-docs/version/2.3/index.html)

[![Scikit-learn](https://img.shields.io/badge/Scikit--learn-1.7+-F7931E?logo=scikit-learn&logoColor=white)](https://scikit-learn.org/stable/whats_new/v1.7.html)

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

This 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.

## Topics

- **NumPy:** Open source project for numerical computing with Python.

- **Pandas:** Open source data analysis and manipulation tool.

- **SciPy:** Tools for array computing and specialized data structures.

- **scikit-learn:** Tools for predictive data analysis.

## Datasets

> 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).

>

> 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).

## Project Setup

This 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`.

- **`uv` Installation**

    ```bash

    curl -LsSf https://astral.sh/uv/install.sh | sh

    ```

- **Clone the Repository:**

    ```bash

    git clone https://github.com/shama-llama/data-science-assignments.git

    cd data-science-assignments

    ```

- **Create a Virtual Environment and Install Dependencies with `uv`:**

    ```bash

    uv venv

    uv pip install -e .

    ```

- **Activate the Virtual Environment:**

    ```bash

    source .venv/bin/activate

    ```

- **Launch Jupyter Notebook:**

    ```bash

    jupyter notebook

    ```

    Navigate to the `notebooks/` directory to run the analysis.

## License

This project is licensed under the terms of the [MIT](LICENSE) open source license.