# NN unable to fit Y = sign-of-tan(X)

**URL:** <https://community.deeplearning.ai/t/nn-unable-to-fit-y-sign-of-tan-x/675370>\
**Category:** Neural Networks and Deep Learning\
**Tags:** week-module-3, coursera-platform\
**Created:** [August 9, 2024, 8:20am UTC](https://community.deeplearning.ai/t/nn-unable-to-fit-y-sign-of-tan-x/675370 "2024-08-09T08:20:15Z")\
**Posts on this page:** 1\
**Showing post:** 8

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**Author:** ![paulinpaloalto](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/paulinpaloalto/32/187_2.png) [@paulinpaloalto](https://community.deeplearning.ai/u/paulinpaloalto)\
**Post date:** [August 9, 2024, 3:39pm UTC](https://community.deeplearning.ai/t/nn-unable-to-fit-y-sign-of-tan-x/675370/8 "2024-08-09T15:39:47Z")

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Interesting. Did you try graphing the results in the same way that they showed for the standard data?

[Here’s another thread](https://community.deeplearning.ai/t/w-3-a1-relu-vs-tanh-accuracy/229609/4) about experimenting with this exercise (using the ReLU activation in that case), which shows the kind of graphing I mean. A picture is (sometimes) worth the proverbial thousand words in terms of seeing what is happening.

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