AI engineering glossary · NumPy pandas visualization
What is np.zeros and np.ones?
np.zeros and np.ones (also called np.zeros, np.ones): Functions that create an array of a given shape filled entirely with 0s or 1s. They are used to preallocate space for results, to initialise weights or counters, and to build masks. Companion functions np.full and np.empty do the same with a chosen value or unset memory.
np.zeros and np.ones: an example
np.zeros((3, 4)) creates a 3 by 4 array of zeros; np.ones(5, dtype=int) creates five integer ones.
Related terms
More NumPy pandas visualization terms
Where you learn it
np.zeros and np.ones is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.