Jon Cherrie, MathWorks
One way to train a deep learning algorithm in MATLAB® is through transfer learning.
In machine learning, transfer learning is the transfer of knowledge from one learned task to a new task. In the context of neural networks, it is transferring learned features of a pretrained network to a new problem.
The common practice in deep learning for such cases is to use a network that is trained on a large data set for a new problem. While the initial layers of the pretrained network can be fixed, the last few layers must be fine-tuned to learn the specific features of the new data set. Transfer learning usually results in faster training times than training a new convolutional neural network because you do not need to estimate all the parameters in the new network.
Recorded: 5 Oct 2016
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .Select web site
You can also select a web site from the following list:
Select the China site (in Chinese or English) for best site performance. Other MathWorks country sites are not optimized for visits from your location.