It is an algorithm used in the training of neural networks. Its function is to adjust the network’s weights based on the difference between the predicted output and the desired output. This process is carried out in reverse through the network, calculating gradients and applying optimization techniques to reduce error and improve the network’s performance during training.

Backpropagation is vital for training deep neural networks, allowing them to learn from data and improve their accuracy in tasks such as image recognition, language processing, and more.

Sign up for the Newsletter
Thank you for subscribing to our newsletter!