NumPy arrays provide a fast and efficient way to store and manipulate data in Python. They are particularly useful for representing data as vectors and matrices in machine learning. Data in NumPy arrays can be accessed directly via column and row indexes, and this is reasonably straightforward. Nevertheless, sometimes we must perform operations on arrays of data such as sum or mean of values by row or column and this requires the axis of the operation to be specified. Unfortunately, […]