transfer learning in keras when input shape is different
You could try adding another layer before the transfer learning model. Just like the last layer, this will update its weights on your dataset and should work fine.
I have a question regarding transfer learning. Let suppose there is a neural network model that takes an input of shape (250,7). I want to initialise the model with the weights of this pre-trained model and then train it on my dataset to update the weights according to my dataset. But my dataset is of shape (251,8). Is there way to initialise the weights using pre-trained model considering my input shape is different? If so how can I do that? Insights will be appreciated.