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更新 Kaggle 入门操作指南 #6

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jiangzhonglian merged 5 commits into from
Nov 10, 2017
Merged

更新 Kaggle 入门操作指南 #6

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8361d26
添加 数字识别的数据集
jiangzhonglian Nov 9, 2017
f8c18be
更新了代码格式
jiangzhonglian Nov 9, 2017
6589c14
更新 Kaggle 入门操作指南
jiangzhonglian Nov 10, 2017
f411c63
优化 kaggle 入门操作指南
jiangzhonglian Nov 10, 2017
1957f44
Merge branch 'master' of https://github.com/apachecn/kaggle
jiangzhonglian Nov 10, 2017
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6 changes: 2 additions & 4 deletions README.md
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# Kaggle

![](static/images/logos/kaggle-logo-gray.png)
![](static/images/logos/kaggle-logo-gray-bigger.jpeg)

> 欢迎任何人参与和完善：一个人可以走的很快，但是一群人却可以走的更远

Expand Down Expand Up @@ -65,8 +65,6 @@ Featured：这些通常是由公司、组织甚至政府赞助的，奖金池最

企业招聘数据科学家的位置



## 活动时间

预计 11月15号前后开展活动，有兴趣的可以提前联系相关的负责人。
Expand All @@ -90,7 +88,7 @@ Featured：这些通常是由公司、组织甚至政府赞助的，奖金池最
* **ApacheCN - 学习机器学习群【629470233】<a target="_blank" href="//shang.qq.com/wpa/qunwpa?idkey=30e5f1123a79867570f665aa3a483ca404b1c3f77737bc01ec520ed5f078ddef"><img border="0" src="static/images/logos/ApacheCN-group.png" alt="ApacheCN - 学习机器学习群【629470233】" title="ApacheCN - 学习机器学习群【629470233】"></a>**
* **Kaggle (数据科学竞赛平台) | [ApacheCN(apache中文网)](http://www.apachecn.org/)**

## 其它中文文档
## [ApacheCN 组织翻译](http://www.apachecn.org/)

* [Beam 中文文档](http://beam.apachecn.org/)
* [Sklearn 0.19 中文文档](http://sklearn.apachecn.org/)
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4 changes: 2 additions & 2 deletions competitions/GettingStarted/DigitRecognizer.md
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# **数字识别**

[**数字识别**](competitions/GettingStarted/DigitRecognizer.md):使用著名的 MNIST 数据来学习计算机视觉基础原理
[**数字识别**](/competitions/GettingStarted/DigitRecognizer.md):使用著名的 MNIST 数据来学习计算机视觉基础原理

## 内容说明：

* MNIST（"修改后的国家标准与技术研究所"）是计算机视觉的事实上的 "hello world" 数据集。自1999年发布以来，手写图像的经典数据集已成为基准分类算法的基础。随着新机器学习技术的出现，MNIST 仍然是研究人员和学习者的可靠资源。
* 在本次比赛中，您的目标是正确识别数以万计手写图像的数字。我们策划了一套教程式的内核，涵盖从回归到神经网络的一切。我们鼓励您尝试使用不同的算法来学习第一手什么是有效的，以及技术如何比较。
* [文档](competitions/GettingStarted/DigitRecognizer.md) [代码](src/python/GettingStarted/DigitRecognizer/dr_knn_pandas.py) **视频-待定**
* [文档](/competitions/GettingStarted/DigitRecognizer.md) [代码](/src/python/GettingStarted/DigitRecognizer/dr_knn_pandas.py) **视频-待定**

##
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