Discussion of article "Neural networks made easy (Part 24): Improving the tool for Transfer Learning"
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im stuck here.. when i load previous model also always say "the file is damaged".. but its work when i use tool from part 23.. can you give me a hint to solve the problem? thanks
New article Neural networks made easy (Part 24): Improving the tool for Transfer Learning has been published:
Author: Dmitriy Gizlyk
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New article Neural networks made easy (Part 24): Improving the tool for Transfer Learning has been published:
In the previous article, we created a tool for creating and editing the architecture of neural networks. Today we will continue working on this tool. We will try to make it more user friendly. This may see, top be a step away form our topic. But don't you think that a well organized workspace plays an important role in achieving the result.
In the previous article in this series, we have created a tool to take advantage of the Transfer Learning technology. As a result of the work done, we got a tool that allows the editing of already trained models. With this tool, we can take any number of neural layers from a pre-rained model. Of course, there are limiting conditions. We take only consecutive layers starting from the initial data layer. The reason for this approach lies in the nature of neural networks. They work well only of the initial data is similar to that used when training the model.
Furthermore, the created tool allows not only editing trained models. It also allows creating completely new ones. This will allow to avoid describing the model architecture in the program code. We will only need to describe a model using the tool. Then we will trail and use the model by uploading the created neural network from a file. This enables experimenting with different architectures without changing the program code. This does not even require the recompilation of the program. You will simply need to change the model file.
Such a useful toll should also be as user friendly as possible. Thus, in this article, we will try to improve its usability.
Author: Dmitriy Gizlyk