cavis/docs/datavec/templates/normalization.md

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---
title: DataVec Normalization
short_title: Normalization
description: Preparing data in the right shape and range for learning.
category: DataVec
weight: 5
---
## Why normalize?
Neural networks work best when the data theyre fed is normalized, constrained to a range between -1 and 1. There are several reasons for that. One is that nets are trained using gradient descent, and their activation functions usually having an active range somewhere between -1 and 1. Even when using an activation function that doesnt saturate quickly, it is still good practice to constrain your values to this range to improve performance.
## Available preprocessors
{{autogenerated}}