10 Questions
In hyperparameter tuning, what is the purpose of a learning rate?
To adjust the step size during optimization
How does dropout contribute to regularization in a CNN?
By randomly dropping connections during training
Which optimization algorithm is known for adapting the learning rate on a per-parameter basis?
Adaptive Moment Estimation (Adam)
What is the primary role of the validation set in hyperparameter tuning?
To evaluate the model on unseen data
How does transfer learning benefit CNNs in practice?
By initializing the network with pre-trained weights
What is the primary challenge addressed by techniques like L2 regularization in CNNs?
Overfitting
In a CNN, what does the term "receptive field" refer to?
The area of the input that a neuron in a particular layer sees
How does a CNN handle input data of varying sizes?
By resizing all input data to a fixed size
Why do CNNs exhibit translation invariance?
Due to parameter sharing in convolutional layers
Which layer type is responsible for introducing non-linear transformations to the input in a CNN?
Activation Layer
Optimizing Performance: Hyperparameter Tuning and Basic CNN Architectures
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