Deep Learning 面接の質問と回答
Question: Explain the concept of fine-tuning in transfer learning and when it is commonly applied.Answer: Fine-tuning in transfer learning involves taking a pre-trained model and further training it on a specific task or dataset. It is commonly applied when the target task is closely related to the source task, and the pre-trained model has already learned useful features. Fine-tuning can improve performance on the target task with less training data. |
復習用に保存
この項目をブックマークに追加したり、難しい内容としてマークしたり、復習セットに入れたりできます。
役に立ちましたか? はい いいえ
ユーザー評価で最も役立つ内容:
- Explain the purpose of an activation function in a neural network.
- What is transfer learning, and how is it used in deep learning?
- What is a convolutional neural network (CNN), and how is it different from a fully connected neural network?