http://d2l.ai/chapter_recurrent-neural-networks/sequence.html

Hi Doctor Li, will there be Tensorflow code posted for Chapter 8 to 17 later? Thank you very much!

Yes, weâ€™re working on it.

Thank you very much! Appreciate it!

Hey guys! For exercise 1. for this section, how does writing a sine and cosine as a differential equation help us, analyze if more or less observations would help or not help with noise?

For exercise 1 part 1 dont we have to also increase the number of epochs with the number of observations? Or is the number of epochs a control variable in this experiment?

What would be a good way to set the features constant in the provided code, so that all of the plots and other code still works?

Hi @smizerex, great question! Since the sine and cosine functions are differentiable, we can calculate each pointâ€™s gradient, and then estimate the next potential point with the gradient times with Î”x. But the estimate point should be with in the range of error đťś–.