How do you use a Pretrained model in deep learning?

On a set of data, a neural network is trained. This data is compiled as the network's "weights," and the network learns from them. It is possible to extract these weights and then apply them to any other neural network. We "transfer" the learned characteristics rather than starting the other neural network from scratch.

How do you use a Pretrained model in deep learning?

We must use our resources more wisely while tackling Deep Learning issues. Particularly when we attempt to address challenging real-world issues in fields like speech and picture recognition. Once your model has a few hidden layers, adding more would require an enormous number of resources.