---
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 they’re 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 doesn’t saturate quickly, it is still good practice to constrain your values to this range to improve performance.

## Available preprocessors

{{autogenerated}}