What are some optimization techniques in NumPy?

What are some optimization techniques in NumPy?

NumPy offers several optimization techniques, such as vectorization, broadcasting, and using built-in functions for efficiency.

Can you explain vectorization in more detail?

Vectorization is the process of converting operations that would typically use loops into array operations, which are faster and more efficient.

What is broadcasting and how does it work?

Broadcasting allows NumPy to perform arithmetic operations on arrays of different shapes by automatically expanding the smaller array to match the larger one.

Are there any specific functions in NumPy that help with optimization?

Yes, functions like numpy.dot(), numpy.sum(), and numpy.mean() are optimized for performance and can handle large datasets efficiently.