Deep Learning 面接の質問と回答
Question: What is the difference between a hyperparameter and a parameter in the context of machine learning models?Answer: Parameters are internal variables learned by the model during training, such as weights and biases. Hyperparameters are external configuration settings that influence the learning process, like the learning rate or the number of hidden layers. They are set before training and are not learned from the 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?