NumPy
data-processing library
Fundamental library for scientific computing in Python
Supported languages
Pros and Cons
Ventajas
- + Fast vectorized operations
- + Foundation of many scientific libraries
- + Excellent documentation
- + Wide ecosystem
- + Very fast vectorized operations
- + Foundation of Python scientific ecosystem
- + Efficient multidimensional arrays
- + Wide collection of mathematical functions
Desventajas
- - Python only
- - No native GPU
- - Only for numerical data
- - No native GPU support
- - Syntax can be confusing at first
Casos de Uso
- Linear algebra
- Numerical processing
- Data analysis
- Machine learning
- Linear algebra and matrices
- Image processing
- Scientific computing
- Base for pandas and scikit-learn
- Numerical simulations