# Tweaking Hyper parameters vs getting more training data

**URL:** <https://community.deeplearning.ai/t/tweaking-hyper-parameters-vs-getting-more-training-data/42191>\
**Category:** AI Discussions\
**Created:** [September 26, 2021, 1:25pm UTC](https://community.deeplearning.ai/t/tweaking-hyper-parameters-vs-getting-more-training-data/42191 "2021-09-26T13:25:48Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Anil\_kumar1](https://avatars.discourse-cdn.com/v4/letter/a/e56c9b/32.png) [@Anil\_kumar1](https://community.deeplearning.ai/u/Anil_kumar1)\
**Post date:** [September 26, 2021, 1:25pm UTC](https://community.deeplearning.ai/t/tweaking-hyper-parameters-vs-getting-more-training-data/42191/1 "2021-09-26T13:25:48Z")

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Hi there,

I often struggle to answer a question. I almost always have very little data at my exposure and most often I end up building an underfit model. If I try to increase the complexity of the network, I see overfitting even after adding regularization in the network. So my question would be is there an approach that could tell me the results that I see are due to low data or due to non-optimal hyper parameters or some issues with my network.

Thanks

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**Author:** ![reinoudbosch](https://avatars.discourse-cdn.com/v4/letter/r/22d042/32.png) [@reinoudbosch](https://community.deeplearning.ai/u/reinoudbosch)\
**Post date:** [May 16, 2023, 10:42am UTC](https://community.deeplearning.ai/t/tweaking-hyper-parameters-vs-getting-more-training-data/42191/2 "2023-05-16T10:42:16Z")

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