In second video of Week 3, Andrew NG talks about which scales to be used for hyperparameters. He gives an example for linear scale, where the range is between 0.0001 and 1. He says that if we were to use a linear scale %10 of our resources would be go to range between 0.0001 - 0.1 and %90 would be gone to 0.1 - 1.

I didn’t understand what does he mean by resources and how he decided that only %10 is in range 0.0001 - 0.1 when we use a linear scale. I would be happy if someone also give some example about this while explaining it.

I understood the 10% probability in a linear scale. But can you please explain how by changing to logarithmic scale raises the probability of getting a value within the range 0.0001 and 0.001