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What is Transfer learning?

A method of applying the knowledge (such as ways of extracting features) that a model acquired on one task to a different task. Starting from the weights of a model pretrained on a large amount of data, the output layer is replaced, or part or all of the model is retrained on data for the new task (fine-tuning). It tends to reach high performance with less data and computation than training from scratch, and is widely used in image recognition and language models.

Japanese name: 転移学習

Transfer learning appears in 1 practice question across 1 topic, including Machine Learning Basics.

Field: Machine Learning Basics

Try it: questions about Transfer learning

Which of the following describes transfer learning, in which a model trained on a large amount of data is used for a different task with little data?

  1. AStarting from the weights of the trained model, the output layer is replaced to suit the new task, or part or all of the model is retrained on the new data (fine-tuning)
  2. BThe trained model is not used; all layers are retrained from randomly initialized weights using only the small amount of data for the new task
  3. CA small model is trained to imitate the outputs of a large model so that the same task can be solved with less computation and memory
Show answer and explanation

Answer: A. Starting from the weights of the trained model, the output layer is replaced to suit the new task, or part or all of the model is retrained on the new data (fine-tuning)

Transfer learning applies the features that a model learned on one task to a different task. For example, the layers near the input of a CNN trained on a large number of images can extract general features such as edges and textures, so only the output layer is replaced and trained for the new task, or the whole network is retrained with a small learning rate (fine-tuning). It tends to reach high performance with less data and computation than training from scratch, and it is also used to adapt language models to specific uses.

Transfer learning in the explanations

Questions that mention Transfer learning (1)

  1. Which of the following describes transfer learning, in which a model trained on a large amount of data is used for a different task with little data?

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Related terms

Convolutional neural network (CNN) Activation function Confusion matrix Cross-validation Gradient descent k-means clustering Overfitting Precision and recall Principal component analysis (PCA) Recurrent neural network (RNN)

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