What are the key differences between NumPy and SciPy?

What are the key differences between NumPy and SciPy?

NumPy is primarily focused on numerical operations and array manipulation, while SciPy builds on NumPy and provides additional functionality for scientific computing, such as optimization, integration, and statistics.

Can you give examples of functions that are unique to SciPy?

Sure! SciPy includes functions for optimization like scipy.optimize.minimize, integration functions like scipy.integrate.quad, and special functions like scipy.special.gamma.

Is it necessary to use both libraries together?

Not necessarily, but using both together is common. NumPy is great for basic array operations, while SciPy enhances those capabilities with more advanced scientific functions.

Which library is better for machine learning?

Neither is specifically designed for machine learning, but NumPy is often used for data manipulation, while SciPy can be useful for optimization tasks in machine learning algorithms.