James_Hennessy

There is no code to read for question 1

1 reply

iamyaa

Hyperparameters are parameters that are set by you before training your model.
They are usually arbitrary and iterative in nature.
Examples:

• batch_size
• no_of_epochs
  *learning rate e.t.c
  I hope it helps.

Ludger_Starke

There is a mismatch between the first code example in section 19.1.1.2 and its explanation. To be correct, either the equation needs to be changed to “stats.loguniform(1e-4, 0.1)” or the text to " which represents a uniform distribution between -4 and 0 in the logarithmic space."

Best regards

Ludger_Starke

It is in chapter 3.2.4