When you start training a new model, you can O start with a high learning rate, so the model could learn faster O Train the model using the entire dataset with many iteration to make sure the model could find the best parameters O try a low learning rate to make sure the model could learn O Ignore the weight regularization
When you start training a new model, you can O start with a high learning rate, so the model could learn faster O Train the model using the entire dataset with many iteration to make sure the model could find the best parameters O try a low learning rate to make sure the model could learn O Ignore the weight regularization
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Transcribed Image Text:When you start training a new model, you can
start with a high learning rate, so the model could
learn faster
Train the model using the entire dataset with
many iteration to make sure the model could find
the best parameters
O try a low learning rate to make sure the model
could learn
Ignore the weight regularization
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