Python for Data Science

NumPy provides efficient array operations, mathematical functions, and is the foundation for most data science libraries.

Pandas provides high-performance, easy-to-use data structures and data analysis tools.

Matplotlib is the foundational plotting library for Python, providing extensive control over visualizations.

Seaborn builds on Matplotlib to provide beautiful statistical visualizations with less code.

Scikit-learn provides efficient tools for machine learning and statistical modeling.

Advanced techniques including feature engineering, model selection, and deployment considerations.