What is the primary advantage of using transfer learning in CNNs?
Practice Questions
1 question
Q1
What is the primary advantage of using transfer learning in CNNs?
It requires less data to train
It speeds up the training process
It improves model accuracy
All of the above
Transfer learning allows models to leverage pre-trained weights, which can lead to faster training, improved accuracy, and reduced data requirements.
Questions & Step-by-step Solutions
1 item
Q
Q: What is the primary advantage of using transfer learning in CNNs?
Solution: Transfer learning allows models to leverage pre-trained weights, which can lead to faster training, improved accuracy, and reduced data requirements.
Steps: 6
Step 1: Understand what transfer learning is. It means using a model that has already been trained on a large dataset.
Step 2: Recognize that CNNs (Convolutional Neural Networks) are a type of model used for image-related tasks.
Step 3: Realize that using pre-trained weights means starting with a model that already knows some features from images.
Step 4: Acknowledge that this can make training faster because the model doesn't start from scratch.
Step 5: Note that using pre-trained weights can improve accuracy since the model has learned useful features already.
Step 6: Understand that transfer learning can reduce the amount of data needed to train the model effectively.
