Question

you're a product manager for a team that's using an artificial neural network to develop your product. one of the data scientists says that the back propagation of errors is correcting for guesses that have a steep gradient descent. what is that saying about the network?

Answer 1

Backpropagation of errors in an artificial neural network corrects for guesses with a steep gradient descent by adjusting weights and biases to minimize errors and improve predictions.

Step-by-step explanation:

The phrase 'correcting for guesses that have a steep gradient descent' in the context of backpropagation of errors in an artificial neural network means that the network is adjusting the weights and biases associated with inputs that resulted in large errors during training. The steep gradient descent refers to the fast adjustment of these weights and biases in order to minimize the errors. Essentially, the network is learning from its mistakes and making the necessary corrections to improve its predictions.