# TeFuirnever/Machine-Learning-in-Action

<https://repo.masters-masters.com/en/repos/TeFuirnever/Machine-Learning-in-Action>

[Home](https://repo.masters-masters.com/en) › [TeFuirnever](https://repo.masters-masters.com/en/owners/TeFuirnever) › [Machine-Learning-in-Action](https://repo.masters-masters.com/en/repos/TeFuirnever/Machine-Learning-in-Action)

TeFuirnever/Machine-Learning-in-Action has 1,026 stars on GitHub. Its RepoMasters card: Beta tier. ⚡️⚡️⚡️《机器学习实战》代码（基于Python3）🚀 Language: Python.

| Field | Value |
| --- | --- |
| Owner | [TeFuirnever](https://repo.masters-masters.com/en/owners/TeFuirnever) |
| Stars | 1,026 |
| Forks | 278 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2019 |
| Topics | knn, decisiontree, naivebayes, logistic, svm, adaboost, regression, regression-trees |
| Tier | [Beta (700 to 1,999 ★)](https://repo.masters-masters.com/en/ranks/box_office) |
| View on GitHub | [TeFuirnever/Machine-Learning-in-Action](https://github.com/TeFuirnever/Machine-Learning-in-Action) |

## Repository

⚡️⚡️⚡️《机器学习实战》代码（基于Python3）🚀

The tier for repos with 700 to 1,999 ★. Published odds per card pulled: 6%. Rarity: Rare.

## Nearby in Python

- [fla-org/native-sparse-attention · ★ 1,026 · Python · Beta](https://repo.masters-masters.com/en/repos/fla-org/native-sparse-attention)
- [dtsola/xiaoyaosearch · ★ 1,026 · Python · Beta](https://repo.masters-masters.com/en/repos/dtsola/xiaoyaosearch)
- [pat-jj/harness-1 · ★ 1,026 · Python · Beta](https://repo.masters-masters.com/en/repos/pat-jj/harness-1)
- [philipperemy/name-dataset · ★ 1,026 · Python · Beta](https://repo.masters-masters.com/en/repos/philipperemy/name-dataset)
- [RiotGames/leaguedirector · ★ 1,026 · Python · Beta](https://repo.masters-masters.com/en/repos/RiotGames/leaguedirector)
- [FullControlXYZ/fullcontrol · ★ 1,026 · Python · Beta](https://repo.masters-masters.com/en/repos/FullControlXYZ/fullcontrol)

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