Create an rng object with np.random.default_rng(), you can seed it for reproducible results. You can draw samples from probability distributions, including from the binomial and normal distributions.

Learn the NumPy trick for generating synthetic data that actually behaves like real data.

RANDOMNESS IS A valuable commodity. Computer models of complex systems ranging from the weather to the stockmarket are voracious consumers of random numbers. Cryptography, too, relies heavily on ...