# Week 2 Feature Scaling - Question

**URL:** <https://community.deeplearning.ai/t/week-2-feature-scaling-question/173062>\
**Category:** Supervised ML: Regression and Classification\
**Tags:** week-module-2\
**Created:** [July 29, 2022, 3:43pm UTC](https://community.deeplearning.ai/t/week-2-feature-scaling-question/173062 "2022-07-29T15:43:40Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![balaji.ambresh](https://sea1.discourse-cdn.com/dlai/user_avatar/community.deeplearning.ai/balaji.ambresh/32/128697_2.png) [@balaji.ambresh](https://community.deeplearning.ai/u/balaji.ambresh)\
**Post date:** [July 29, 2022, 5:12pm UTC](https://community.deeplearning.ai/t/week-2-feature-scaling-question/173062/2 "2022-07-29T17:12:39Z")

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Does [this](https://community.deeplearning.ai/t/c1-w2-lab1-exercise-7-why-does-normalization-change-the-results-so-much/136200) help?

Choice of feature scaling depends on the algorithm in use. For neural networks, feature scaling is always done. For tree based algorithms, feature scaling is not done.

Feature scaling is never done for target labels.

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