What is the difference between transfer learning and training from scratch?
An example of an AI chatbot conversation about transfer learning vs training from scratch.
What is the difference between transfer learning and training from scratch?
Transfer learning involves using a pre-trained model on a new task, while training from scratch means building a model from the ground up.
When should I use transfer learning instead of training from scratch?
Use transfer learning when you have limited data for your task, as it leverages knowledge from related tasks.
Can you give me an example of transfer learning in action?
Sure! A common example is using a model trained on ImageNet to classify medical images, adapting it to a new domain.
What are the advantages of training from scratch?
Training from scratch allows for complete control over the model architecture and can lead to better performance on specific tasks.
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