Does dataset size affect the performance of alexnet architecture? For small dataset is data augmentation necessary if we want to use alexnet or mobilenet architectures in deep learning
Pokedox challenge
Yes dataset size really affects performance of models having large number of parameters.
That is where transfer learning comes into role play, when we are limited by the size of dataset. We can perform data augmentation, but upto a certain limit only, means you should not do over sampling. We can use transfer learning here, by freezing the initial layers and fine tuning others. This helps us to achieve better reliable performances for the models like alexnet, resnet, mobilenet etc.
Hope this helped you. 
I hope I’ve cleared your doubt. I ask you to please rate your experience here
Your feedback is very important. It helps us improve our platform and hence provide you
the learning experience you deserve.
On the off chance, you still have some questions or not find the answers satisfactory, you may reopen
the doubt.