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100-Days-Of-ML-Code/FAQ.MD
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# 常见问题解答
欢迎到Issues提问
### 1. “拆分数据”和“特征缩放”的顺序
可以先“拆分数据”再“特征缩放”但需要使用训练集的fit参数去transform测试集以保证参数相同。
详见[issue#41](https://github.com/MachineLearning100/100-Days-Of-ML-Code/issues/41)。
### 2. 3Blue1Brown视频
原作中提到的YouTube视频在B站有[官方中文版](https://space.bilibili.com/88461692/#/)README的链接也是到B站。
感谢网友在[issue#45](https://github.com/MachineLearning100/100-Days-Of-ML-Code/issues/45)的反馈。
### 3. Deep Learning basics with Python, TensorFlow and Keras
正在翻译[文字版](https://pythonprogramming.net/introduction-deep-learning-python-tensorflow-keras/),敬请期待。
详见[issue#52](https://github.com/MachineLearning100/100-Days-Of-ML-Code/issues/52)。
### 4.《Python数据科学手册》
**[高清中文版pdf](https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Other%20Docs/Python%E6%95%B0%E6%8D%AE%E7%A7%91%E5%AD%A6%E6%89%8B%E5%86%8C.zip)**[Jupyter notebooks](https://github.com/jakevdp/PythonDataScienceHandbook)。
<br>仅作为个人学习,不能用于商业用途。
### 5. 微信群
见[issuse#59](https://github.com/MachineLearning100/100-Days-Of-ML-Code/issues/59)
### 6. 常用工具推荐
见[issuse#60](https://github.com/MLEveryday/100-Days-Of-ML-Code/issues/60)