What is the difference between broadcasting and replication in NumPy?

What is the difference between broadcasting and replication in NumPy?

Broadcasting allows NumPy to work with arrays of different shapes during arithmetic operations, while replication involves duplicating data to match shapes.

Can you give me an example of broadcasting in action?

Sure! If you have an array of shape (3, 1) and another of shape (1, 4), broadcasting allows them to be combined to create an array of shape (3, 4).

What about replication? How does that work?

Replication involves creating copies of an array to match the shape of another array. For instance, if you replicate a (2,) array to match a (2, 3) shape, you'll get two rows of the original array.

When should I use broadcasting instead of replication?

Use broadcasting when you want to perform operations without increasing memory usage, as it is more efficient than replication.