The weights and inputs are multiplied and return an output involving 0 and 1. When the network didn't accurately acknowledge a certain sample, an algorithm would change the weights.[144] This way the algorithm can make sure parameters more influential, until finally it decides the right mathematical manipulation to completely course https://deeplearningai20852.blogkoo.com/the-best-side-of-deep-learning-ai-45789359