Building well-performing neural networks is a complex task that requires specific skills, knowledge, resources and data to succeed. That’s why we have taken a big leap towards reducing the complexity of building deep learning models and helping you succeed with deep learning on the Peltarion Platform.
Pretrained blocks: Reducing the complexity of building DL models
This is how
We've added a pretrained VGG feature extractor as one of the first pretrained networks, trained on 1.2M ImageNet images.
Why pretrained blocks?
Pretrained blocks, called Pretrained snippets on the platform, is an extremely powerful feature that has numerous benefits like reducing the time and skills needed to get started, lowering the costs and supporting many companies or individuals who don't own large datasets, enabling them to get value in their specific domain or the problem they’re trying to solve. This is due to the fact that pretrained networks have already learned the basic representations of data structures and can be trained on a small domain-specific dataset to provide value.
When using the VGG feature extractor, you will notice that we have also grouped the deep neural network blocks to hide the unnecessary complexity and fit the model in the canvas. You can always expand and collapse the groups, or just add additional layers in the end to adjust the model functions.