What are advantages or disadvantages of training deep learning model from scratch?
(Suggestions and edits will be appreciated)

let us discuss advantages of training a deep learning model from scratch:


Building and training NN from scratch is of a great use in the research field.
You will know your model to the most basics and can modify it in case needed as per the requirements.
It will be more efficient in terms of size and training time(because there may be less number of layers as compared to any pretrained model trained for more than one purpose).Best example is VGG16.In case of VGG16 it is trained for 1000 different categories and even if we want only 2 categories we have to train the whole model,because we can't change the layers without deep knowledge about the architecture of VGG16.
For any beginner(like me) it will be beneficial to start building from scratch and the use the pre-trained model.
Don't require mastery in Deep Learning to use pretrained models.


Disadvantages:


Many pre-trained models are trained for less or mode different purposes,so may not be suitable in some cases.
It will take large amount of resources(time and computation power) to train big models from scratch.