# AutoViML/featurewiz

<https://repo.masters-masters.com/en/repos/AutoViML/featurewiz>

[Home](https://repo.masters-masters.com/en) › [AutoViML](https://repo.masters-masters.com/en/owners/AutoViML) › [featurewiz](https://repo.masters-masters.com/en/repos/AutoViML/featurewiz)

AutoViML/featurewiz has 685 stars on GitHub. Its RepoMasters card: Alpha tier. Use advanced feature engineering strategies and select best features from your…

| Field | Value |
| --- | --- |
| Owner | [AutoViML](https://repo.masters-masters.com/en/owners/AutoViML) |
| Stars | 685 |
| Forks | 100 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2020 |
| Topics | feature-engineering, categorical-variables, best-encoders, feature-engg, rfe, rfecv, feature-extraction, feature-selection, featuretools, xgboost |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [AutoViML/featurewiz](https://github.com/AutoViML/featurewiz) |

## Repository

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.
