# floodsung/wechat\_jump\_end\_to\_end

<https://repo.masters-masters.com/en/repos/floodsung/wechat_jump_end_to_end>

[Home](https://repo.masters-masters.com/en) › [floodsung](https://repo.masters-masters.com/en/owners/floodsung) › [wechat\_jump\_end\_to\_end](https://repo.masters-masters.com/en/repos/floodsung/wechat_jump_end_to_end)

floodsung/wechat\_jump\_end\_to\_end has 182 stars on GitHub. Its RepoMasters card: Prototype tier. Playing Wechat Jump Game with End-to-End Convolutional Neural…

| Field | Value |
| --- | --- |
| Owner | [floodsung](https://repo.masters-masters.com/en/owners/floodsung) |
| Stars | 182 |
| Forks | 35 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | MIT |
| Created | 2018 |
| Topics | deep-learning, wechat-jump-game |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [floodsung/wechat\_jump\_end\_to\_end](https://github.com/floodsung/wechat_jump_end_to_end) |

## Repository

Playing Wechat Jump Game with End-to-End Convolutional Neural Networks

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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