Data-Science is a repository containing my data science projects, showcasing my skills in data analysis, visualization, and machine learning. Built primarily with Python, this collection includes various scripts, Jupyter Notebooks, and datasets to demonstrate my expertise in extracting insights from data.

• Perform data analysis to uncover trends, patterns, and actionable insights.
• Create visualizations to effectively communicate data findings.
• Apply machine learning techniques to build predictive models (if applicable).
• Document and share my data science workflow through code and notebooks.

• Programming Language:
  • Python 3.x
• Libraries:
  • Pandas (for data processing and analysis)
  • NumPy (for numerical computations)
  • Matplotlib (for data visualization)
  • Seaborn (for statistical visualizations)
  • Scikit-learn (for machine learning, if applicable)
• Environment:
  • Jupyter Notebook
  • Virtualenv / Conda (for environment management)
• Version Control:
  • Git & GitHub

• 🔧 Clone the repository:

  git clone https://github.com/tphathuin1802/data-science.git
  cd data-science