title: When should you use pretrained weights when training deep learning models?
body: <p>I am interested in training a range of image and object detection models and I am wondering what the general rule of when to use pretrained weights of a network like VGG16 is. </p>
  
  <p>For example, it seems obvious that fine-tuning pre-trained VGG16 imagenet model weights is helpful you are looking for a subset ie.  Cats and Dogs. </p>
  
  <p>However it seems less clear to me whether using these pretrained weights is a good idea if you are training an image classifier with 300 classes with only some of them being subsets of the classes in the pretrained model. </p>
  
  <p>What is the intuition around this? </p>