Transfer learning for Digit Classification
Transfer learning for Digit Classification
This is a trivial project demonstrating the subtle differences between multi class logistic regression, multilayered perceptrons+softmax(trained using cross entropy loss) and CNNs+softmax(trained using cross entropy loss) architectures in classifying digits. It also shows how well certain models can transfer over to other datasets provided the data distributions of the two are similar.
