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Sagot :
You define your output layer and the desired number of classes when you add your DNN at the bottom of the network.
Transfer learning: What is it?
- A pre-trained model is used as the foundation for a new model in the machine learning technique known as transfer learning.
- Simply expressed, an optimization that enables quick progress when modeling the second task is applied to a model that was trained on the first, unrelated job.
What varieties of transfer learning are there?
There are three varieties of training transfer:
- Training improves performance in the desired career or function, which is a positive transfer.
- Negative Transfer: Training results in lower performance in the intended position or function.
- Zero Transfer: Training has no effect on performance in the intended job or role, either up or down.
What is an example of transfer learning?
- For instance, if you trained a straightforward classifier to determine whether a picture has a backpack, you might use that knowledge to recognize other things, like sunglasses.
- With transfer learning, we essentially attempt to apply the knowledge we have gained to new situations in order to comprehend the concepts more fully.
learn more about transfer learning here
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