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对外技术分享	https://github.com/valueable/Reflection_Summary/tree/master/%E5%AF%B9%E5%A4%96%E6%8A%80%E6%9C%AF%E5%88%86%E4%BA%AB
推荐	https://github.com/valueable/Reflection_Summary/tree/master/%E6%8E%A8%E8%8D%90
推荐	https://github.com/valueable/Reflection_Summary/tree/master/%E6%8E%A8%E8%8D%90
数学	https://github.com/valueable/Reflection_Summary/tree/master/%E6%95%B0%E5%AD%A6
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数据预处理	https://github.com/valueable/Reflection_Summary/tree/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86
数据预处理	https://github.com/valueable/Reflection_Summary/tree/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86
机器学习	https://github.com/valueable/Reflection_Summary/tree/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0
机器学习	https://github.com/valueable/Reflection_Summary/tree/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0
深度学习	https://github.com/valueable/Reflection_Summary/tree/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0
深度学习	https://github.com/valueable/Reflection_Summary/tree/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0
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自然语言处理	https://github.com/valueable/Reflection_Summary/tree/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86
LICENSE	https://github.com/valueable/Reflection_Summary/blob/master/LICENSE
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README.md	https://github.com/valueable/Reflection_Summary/blob/master/README.md
README.md	https://github.com/valueable/Reflection_Summary/blob/master/README.md
README	https://github.com/valueable/Reflection_Summary
MIT license	https://github.com/valueable/Reflection_Summary
	https://github.com/valueable/Reflection_Summary#reflection_summary
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	https://github.com/valueable/Reflection_Summary#基础概念
解释方差	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L1
解释偏差	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L4
模型训练为什么要引入偏差和方差？请理论论证	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L7
什么情况下引发高方差	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L26
如何解决高方差问题	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L31
以上方法是否一定有效	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L36
如何解决高偏差问题	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L44
以上方法是否一定有效	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L51
遇到过的机器学习中的偏差与方差问题	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L56
就理论角度论证Bagging、Boosting的方差偏差问题	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L60
遇到过的深度学习中的偏差与方差问题	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L88
方差、偏差与模型的复杂度之间的关系	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE/%E6%96%B9%E5%B7%AE%E4%B8%8E%E5%81%8F%E5%B7%AE.md#L96
什么叫生成模型	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B.md#L96
什么叫判别模型	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B.md#L96
什么时候会选择生成/判别模型	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B.md#L96
CRF/朴素贝叶斯/EM/最大熵模型/马尔科夫随机场/混合高斯模型	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B.md#L96
我的理解	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B/%E7%94%9F%E6%88%90%E4%B8%8E%E5%88%A4%E5%88%AB%E6%A8%A1%E5%9E%8B.md#L96
写出全概率公式&贝叶斯公式	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87.md#L96
说说你怎么理解为什么有全概率公式&贝叶斯公式	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87.md#L96
什么是先验概率	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87.md#L96
什么是后验概率	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87.md#L96
经典概率题	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87/%E5%85%88%E9%AA%8C%E6%A6%82%E7%8E%87%E5%92%8C%E5%90%8E%E9%AA%8C%E6%A6%82%E7%8E%87.md#L96
极大似然估计 - MLE	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E9%A2%91%E7%8E%87%E6%A6%82%E7%8E%87/%E9%A2%91%E7%8E%87%E6%A6%82%E7%8E%87.md#L96
最大后验估计 - MAP	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E9%A2%91%E7%8E%87%E6%A6%82%E7%8E%87/%E9%A2%91%E7%8E%87%E6%A6%82%E7%8E%87.md#L96
极大似然估计与最大后验概率的区别	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E9%A2%91%E7%8E%87%E6%A6%82%E7%8E%87/%E9%A2%91%E7%8E%87%E6%A6%82%E7%8E%87.md#L96
到底什么是似然什么是概率估计	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/%E9%A2%91%E7%8E%87%E6%A6%82%E7%8E%87/%E9%A2%91%E7%8E%87%E6%A6%82%E7%8E%87.md#L96
AutoML问题构成	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoML.md#L96
特征工程选择思路	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoML.md#L96
模型相关的选择思路	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoML.md#L96
常见梯度处理思路	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoML.md#L96
AutoML参数选择所使用的方法	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoML.md#L96
讲讲贝叶斯优化如何在automl上应用	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoML.md#L96
以高斯过程为例，超参搜索的f的最优解求解acquisition function有哪些	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoML.md#L96
高斯过程回归手记	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/%E9%AB%98%E6%96%AF%E8%BF%87%E7%A8%8B%E5%9B%9E%E5%BD%92
AutoSklearn详解手记	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoSklearn%E8%AF%A6%E8%A7%A3
AutoML常规思路手记	https://github.com/valueable/Reflection_Summary/blob/master/%E5%9F%BA%E7%A1%80%E6%A6%82%E5%BF%B5/AutoML/AutoML%E5%B8%B8%E8%A7%84%E6%80%9D%E8%B7%AF
	https://github.com/valueable/Reflection_Summary#数学
期望	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%95%B0%E6%8D%AE%E8%B4%A8%E9%87%8F/%E6%9C%9F%E6%9C%9B%E3%80%81%E6%96%B9%E5%B7%AE%E3%80%81%E6%A0%87%E5%87%86%E5%B7%AE%E5%92%8C%E5%8D%8F%E6%96%B9%E5%B7%AE.md#L1
方差	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%95%B0%E6%8D%AE%E8%B4%A8%E9%87%8F/%E6%9C%9F%E6%9C%9B%E3%80%81%E6%96%B9%E5%B7%AE%E3%80%81%E6%A0%87%E5%87%86%E5%B7%AE%E5%92%8C%E5%8D%8F%E6%96%B9%E5%B7%AE.md#L4
标准差	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%95%B0%E6%8D%AE%E8%B4%A8%E9%87%8F/%E6%9C%9F%E6%9C%9B%E3%80%81%E6%96%B9%E5%B7%AE%E3%80%81%E6%A0%87%E5%87%86%E5%B7%AE%E5%92%8C%E5%8D%8F%E6%96%B9%E5%B7%AE.md#L9
协方差	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%95%B0%E6%8D%AE%E8%B4%A8%E9%87%8F/%E6%9C%9F%E6%9C%9B%E3%80%81%E6%96%B9%E5%B7%AE%E3%80%81%E6%A0%87%E5%87%86%E5%B7%AE%E5%92%8C%E5%8D%8F%E6%96%B9%E5%B7%AE.md#L11
相关系数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%95%B0%E6%8D%AE%E8%B4%A8%E9%87%8F/%E6%9C%9F%E6%9C%9B%E3%80%81%E6%96%B9%E5%B7%AE%E3%80%81%E6%A0%87%E5%87%86%E5%B7%AE%E5%92%8C%E5%8D%8F%E6%96%B9%E5%B7%AE.md#L11
辗转相除法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%9C%80%E5%A4%A7%E5%85%AC%E7%BA%A6%E6%95%B0%E9%97%AE%E9%A2%98/gcd.md#L1
其他方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%9C%80%E5%A4%A7%E5%85%AC%E7%BA%A6%E6%95%B0%E9%97%AE%E9%A2%98/gcd.md#L1
迭代公式推导	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E7%89%9B%E9%A1%BF%E6%B3%95/%E7%89%9B%E9%A1%BF%E8%BF%AD%E4%BB%A3%E6%B3%95%E6%B1%82%E5%B9%B3%E6%96%B9%E6%A0%B9.md#L1
实现它	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E7%89%9B%E9%A1%BF%E6%B3%95/%E7%89%9B%E9%A1%BF%E8%BF%AD%E4%BB%A3%E6%B3%95%E6%B1%82%E5%B9%B3%E6%96%B9%E6%A0%B9.md#L1
均匀分布	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83.md#L1
伯努利分布	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83.md#L1
二项分布	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83.md#L1
高斯分布	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83.md#L1
拉普拉斯分布	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83.md#L1
泊松分布	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83/%E6%A6%82%E7%8E%87%E5%AF%86%E5%BA%A6%E5%88%86%E5%B8%83.md#L1
平面曲线的切线	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%B9%B3%E9%9D%A2%E6%9B%B2%E7%BA%BF%E7%9A%84%E5%88%87%E7%BA%BF%E5%92%8C%E6%B3%95%E7%BA%BF/%E5%B9%B3%E9%9D%A2%E6%9B%B2%E7%BA%BF%E7%9A%84%E5%88%87%E7%BA%BF%E5%92%8C%E6%B3%95%E7%BA%BF.md#L1
平面曲线的法线	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%B9%B3%E9%9D%A2%E6%9B%B2%E7%BA%BF%E7%9A%84%E5%88%87%E7%BA%BF%E5%92%8C%E6%B3%95%E7%BA%BF/%E5%B9%B3%E9%9D%A2%E6%9B%B2%E7%BA%BF%E7%9A%84%E5%88%87%E7%BA%BF%E5%92%8C%E6%B3%95%E7%BA%BF.md#L1
四则运算	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%AF%BC%E6%95%B0/%E5%AF%BC%E6%95%B0.md#L1
常见导数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%AF%BC%E6%95%B0/%E5%AF%BC%E6%95%B0.md#L1
复合函数的运算法则	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%AF%BC%E6%95%B0/%E5%AF%BC%E6%95%B0.md#L1
莱布尼兹公式	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%AF%BC%E6%95%B0/%E5%AF%BC%E6%95%B0.md#L1
费马定理	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%BE%AE%E5%88%86%E4%B8%AD%E5%80%BC%E5%AE%9A%E7%90%86/%E5%BE%AE%E5%88%86%E4%B8%AD%E5%80%BC%E5%AE%9A%E7%90%86.md#L1
拉格朗日中值定理	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%BE%AE%E5%88%86%E4%B8%AD%E5%80%BC%E5%AE%9A%E7%90%86/%E5%BE%AE%E5%88%86%E4%B8%AD%E5%80%BC%E5%AE%9A%E7%90%86.md#L1
柯西中值定理	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E5%BE%AE%E5%88%86%E4%B8%AD%E5%80%BC%E5%AE%9A%E7%90%86/%E5%BE%AE%E5%88%86%E4%B8%AD%E5%80%BC%E5%AE%9A%E7%90%86.md#L1
泰勒公式	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%B3%B0%E5%8B%92%E5%85%AC%E5%BC%8F/%E6%B3%B0%E5%8B%92%E5%85%AC%E5%BC%8F.md#L1
欧拉公式	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%AC%A7%E6%8B%89%E5%85%AC%E5%BC%8F/%E6%AC%A7%E6%8B%89%E5%85%AC%E5%BC%8F.md#L1
范数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E7%9F%A9%E9%98%B5/%E7%9F%A9%E9%98%B5.md#L1
特征值分解，特征向量	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E7%9F%A9%E9%98%B5/%E7%9F%A9%E9%98%B5.md#L1
正定性	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E7%9F%A9%E9%98%B5/%E7%9F%A9%E9%98%B5.md#L1
条件概率	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
独立	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
概率基础公式	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
全概率	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
贝叶斯	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
切比雪夫不等式	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
抽球	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
纸牌问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
棍子/绳子问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
贝叶斯题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
选择时间问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
0~1均匀分布的随机器如何变化成均值为0，方差为1的随机器	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
抽红蓝球球	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E5%AD%A6/%E6%A6%82%E7%8E%87%E8%AE%BA/%E6%A6%82%E7%8E%87%E8%AE%BA.md#L1
	https://github.com/valueable/Reflection_Summary#数据预处理
为什么要对数据进行采样	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E6%95%B0%E6%8D%AE%E5%B9%B3%E8%A1%A1/%E9%87%87%E6%A0%B7.md#L1
是否一定需要对原始数据进行采样平衡	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E6%95%B0%E6%8D%AE%E5%B9%B3%E8%A1%A1/%E9%87%87%E6%A0%B7.md#L6
有哪些常见的采样方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E6%95%B0%E6%8D%AE%E5%B9%B3%E8%A1%A1/%E9%87%87%E6%A0%B7.md#L11
能否避免采样	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E6%95%B0%E6%8D%AE%E5%B9%B3%E8%A1%A1/%E9%87%87%E6%A0%B7.md#L36
你平时怎么用采样方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E6%95%B0%E6%8D%AE%E5%B9%B3%E8%A1%A1/%E9%87%87%E6%A0%B7.md#L39
统计方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E8%AF%86%E5%88%AB.md#L1
矩阵分解方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E8%AF%86%E5%88%AB.md#L21
特征值和特征向量的本质是什么	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E8%AF%86%E5%88%AB.md#L33
矩阵乘法的实际意义	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E8%AF%86%E5%88%AB.md#L37
密度的离群点检测	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E8%AF%86%E5%88%AB.md#L41
聚类的离群点检测	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E8%AF%86%E5%88%AB.md#L52
如何处理异常点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E5%A4%84%E7%90%86/%E5%BC%82%E5%B8%B8%E7%82%B9%E8%AF%86%E5%88%AB.md#L56
是不是一定需要对缺失值处理	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86.md#L1
直接填充方法有哪些	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86.md#L4
模型插值方法有哪些？及方法的问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86.md#L10
如何直接离散化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86.md#L14
hold位填充方法有哪些	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86.md#L17
怎么理解分布补全	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86.md#L22
random方法使用前提	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86.md#L25
总结	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86/%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A4%84%E7%90%86.md#L28
为什么要做特征选择	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E9%80%89%E6%8B%A9/%E7%89%B9%E5%BE%81%E9%80%89%E6%8B%A9.md#L1
从哪些方面可以做特征选择	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E9%80%89%E6%8B%A9/%E7%89%B9%E5%BE%81%E9%80%89%E6%8B%A9.md#L6
既然说了两个方向，分别介绍一些吧	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E9%80%89%E6%8B%A9/%E7%89%B9%E5%BE%81%E9%80%89%E6%8B%A9.md#L10
为什么需要对数据进行变换	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96/%E6%95%B0%E6%8D%AE%E5%8F%98%E6%8D%A2.md#L1
归一化和标准化之间的关系	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96/%E6%95%B0%E6%8D%AE%E5%8F%98%E6%8D%A2.md#L6
连续特征常用方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96/%E6%95%B0%E6%8D%AE%E5%8F%98%E6%8D%A2.md#L20
离散特征常用方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96/%E6%95%B0%E6%8D%AE%E5%8F%98%E6%8D%A2.md#L71
文本特征	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96/%E6%95%B0%E6%8D%AE%E5%8F%98%E6%8D%A2.md#L88
画一个最简单的最快速能实现的框架	https://github.com/valueable/Reflection_Summary/blob/master/%E6%95%B0%E6%8D%AE%E9%A2%84%E5%A4%84%E7%90%86/%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96/%E6%95%B0%E6%8D%AE%E5%8F%98%E6%8D%A2.md#L164
	https://github.com/valueable/Reflection_Summary#机器学习
请问从EM角度理解kmeans	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%81%9A%E7%B1%BB/kmeans.md#L164
为什么kmeans一定会收敛	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%81%9A%E7%B1%BB/kmeans.md#L164
kmeans初始点除了随机选取之外的方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%81%9A%E7%B1%BB/kmeans.md#L164
损失函数是啥	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92.md#L164
最小二乘/梯度下降手推	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92.md#L164
介绍一下岭回归	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92.md#L164
什么时候使用岭回归	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92.md#L164
什么时候用Lasso回归	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92/%E7%BA%BF%E6%80%A7%E5%9B%9E%E5%BD%92.md#L164
logistic分布函数和密度函数，手绘大概的图像	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR推导，基础5连问	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
梯度下降如何并行化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR明明是分类模型为什么叫回归	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
为什么LR可以用来做CTR预估	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
满足什么样条件的数据用LR最好	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR为什么使用sigmoid函数作为激活函数？其他函数不行吗	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
利用几率odds的意义在哪	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
Sigmoid函数到底起了什么作用	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR为什么要使用极大似然函数，交互熵作为损失函数？那为什么不选平方损失函数的呢	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR中若标签为+1和-1，损失函数如何推导？	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
如果有很多的特征高度相关或者说有一个特征重复了100遍，会造成怎样的影响	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
为什么要避免共线性	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR可以用核么？可以怎么用	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR中的L1/L2正则项是啥	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
lr加l1还是l2好	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
正则化是依据什么理论实现模型优化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR可以用来处理非线性问题么	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
为什么LR需要归一化或者取对数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
为什么LR把特征离散化后效果更好？离散化的好处有哪些	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
逻辑回归估计参数时的目标函数逻辑回归的值表示概率吗	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR对比万物	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR梯度下降方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
LR的优缺点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
除了做分类，你还会用LR做什么	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
你有用过sklearn中的lr么？你用的是哪个包	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
看过源码么？为什么去看	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
谈一下sklearn.linear_model.LogisticRegression中的penalty和solver的选择	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
谈一下sklearn.linear_model.LogisticRegression中对多分类是怎么处理的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
我的总结	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%80%BB%E8%BE%91%E5%9B%9E%E5%BD%92/lr.md#L164
常见决策树	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
简述决策树构建过程	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
详述信息熵计算方法及存在问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
详述信息增益计算方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
详述信息增益率计算方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
解释Gini系数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
ID3存在的问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
C4.5相对于ID3的改进点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
CART的连续特征改进点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
CART分类树建立算法的具体流程	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
CART回归树建立算法的具体流程	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
CART输出结果的逻辑	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
CART树算法的剪枝过程是怎么样的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
树形结构为何不需要归一化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
决策树的优缺点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E5%86%B3%E7%AD%96%E6%A0%91/%E5%86%B3%E7%AD%96%E6%A0%91.md#L164
解释一下朴素贝叶斯中考虑到的条件独立假设	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%B4%9D%E5%8F%B6%E6%96%AF/%E8%B4%9D%E5%8F%B6%E6%96%AF.md#L164
讲一讲你眼中的贝叶斯公式和朴素贝叶斯分类差别	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%B4%9D%E5%8F%B6%E6%96%AF/%E8%B4%9D%E5%8F%B6%E6%96%AF.md#L164
朴素贝叶斯中出现的常见模型有哪些	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%B4%9D%E5%8F%B6%E6%96%AF/%E8%B4%9D%E5%8F%B6%E6%96%AF.md#L164
出现估计概率值为 0 怎么处理	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%B4%9D%E5%8F%B6%E6%96%AF/%E8%B4%9D%E5%8F%B6%E6%96%AF.md#L164
朴素贝叶斯的优缺点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%B4%9D%E5%8F%B6%E6%96%AF/%E8%B4%9D%E5%8F%B6%E6%96%AF.md#L164
朴素贝叶斯与 LR 区别	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E8%B4%9D%E5%8F%B6%E6%96%AF/%E8%B4%9D%E5%8F%B6%E6%96%AF.md#L164
解释下随机森林	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
随机森林用的是什么树	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
随机森林的生成过程	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
解释下随机森林节点的分裂策略	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
随机森林的损失函数是什么	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
为了防止随机森林过拟合可以怎么做	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
随机森林特征选择的过程	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
是否用过随机森林，有什么技巧	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
RF的参数有哪些，如何调参	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
RF的优缺点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97/%E9%9A%8F%E6%9C%BA%E6%A3%AE%E6%9E%97.md#L164
介绍一下Boosting的思想	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
最小二乘回归树的切分过程是怎么样的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
有哪些直接利用了Boosting思想的树模型	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
gbdt和boostingtree的boosting分别体现在哪里	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
gbdt的中的tree是什么tree？有什么特征	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
常用回归问题的损失函数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
常用分类问题的损失函数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
什么是gbdt中的残差的负梯度	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
如何用损失函数的负梯度实现gbdt	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
拟合损失函数的负梯度为什么是可行的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
即便拟合负梯度是可行的，为什么不直接拟合残差？拟合负梯度好在哪里	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
Shrinkage收缩的作用	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
feature属性会被重复多次使用么	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
gbdt如何进行正则化的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
为什么集成算法大多使用树类模型作为基学习器？或者说，为什么集成学习可以在树类模型上取得成功	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
gbdt的优缺点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
gbdt和randomforest区别	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
GBDT和LR的差异	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/GBDT.md#L164
xgboost对比gbdt/boosting Tree有了哪些方向上的优化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xgboost和gbdt的区别	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xgboost优化目标/损失函数改变成什么样	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xgboost如何使用MAE或MAPE作为目标函数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xgboost如何寻找分裂节点的候选集	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xgboost如何处理缺失值	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xgboost在计算速度上有了哪些点上提升	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xgboost特征重要性是如何得到的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xGBoost中如何对树进行剪枝	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xGBoost模型如果过拟合了怎么解决	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
xgboost如何调参数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/Xgboost.md#L164
XGboost缺点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/LightGBM.md#L164
LightGBM对Xgboost的优化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/LightGBM.md#L164
LightGBM亮点	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E9%9B%86%E6%88%90%E5%AD%A6%E4%B9%A0/LightGBM.md#L164
简单介绍SVM	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
什么叫最优超平面	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
什么是支持向量	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
SVM 和全部数据有关还是和局部数据有关	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
加大训练数据量一定能提高SVM准确率吗	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
如何解决多分类问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
可以做回归吗，怎么做	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
SVM 能解决哪些问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
介绍一下你知道的不同的SVM分类器	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
什么叫软间隔	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
SVM 软间隔与硬间隔表达式	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
SVM原问题和对偶问题的关系/解释原问题和对偶问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
为什么要把原问题转换为对偶问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
为什么求解对偶问题更加高效	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
alpha系数有多少个	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
KKT限制条件，KKT条件有哪些，完整描述	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
引入拉格朗日的优化方法后的损失函数解释	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
核函数的作用是啥	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
核函数的种类和应用场景	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
如何选择核函数	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
常用核函数的定义	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
核函数需要满足什么条件	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
为什么在数据量大的情况下常常用lr代替核SVM	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
高斯核可以升到多少维？为什么	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
SVM和逻辑斯特回归对同一样本A进行训练，如果某类中增加一些数据点，那么原来的决策边界分别会怎么变化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
各种机器学习的应用场景分别是什么？例如，k近邻,贝叶斯，决策树，svm，逻辑斯蒂回归	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
Linear SVM 和 LR 有什么异同	https://github.com/valueable/Reflection_Summary/blob/master/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA.md#L164
	https://github.com/valueable/Reflection_Summary#深度学习
为什么要用深度召回	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E6%A1%86%E6%9E%B6.md#L164
dropout如何作用的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/dropout.md#L164
L1为什么在深度学习中不常用	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/dropout.md#L164
用贝叶斯机率说明Dropout的原理	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/dropout.md#L164
为什么有效	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/dropout.md#L164
你觉得bn过程是什么样的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/batch_normalization.md#L164
手写一下bn过程	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/batch_normalization.md#L164
知道LN么？讲讲原理	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/batch_normalization.md#L164
介绍残差网络	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E6%AE%8B%E5%B7%AE%E7%BD%91%E7%BB%9C.md#L164
残差网络为什么能解决梯度消失的问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E6%AE%8B%E5%B7%AE%E7%BD%91%E7%BB%9C.md#L164
残差网络残差作用	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E6%AE%8B%E5%B7%AE%E7%BD%91%E7%BB%9C.md#L164
你平时有用过么？或者你在哪些地方遇到了	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E6%AE%8B%E5%B7%AE%E7%BD%91%E7%BB%9C.md#L164
Attention对比RNN和CNN，分别有哪点你觉得的优势	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/Attention.md#L164
写出Attention的公式	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/Attention.md#L164
解释你怎么理解Attention的公式的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/Attention.md#L164
Attention模型怎么避免词袋模型的顺序问题的困境的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/Attention.md#L164
Attention机制，里面的q,k,v分别代表什么	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/Attention.md#L164
为什么self-attention可以替代seq2seq	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/Attention.md#L164
维度与点积大小的关系是怎么样的，为什么使用维度的根号来放缩	https://github.com/valueable/Reflection_Summary/blob/master/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/Attention.md#L164
	https://github.com/valueable/Reflection_Summary#自然语言处理
GolVe的损失函数	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/GloVe.md#L164
解释GolVe的损失函数	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/GloVe.md#L164
为什么GolVe会用的相对比W2V少	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/GloVe.md#L164
从隐藏层到输出的Softmax层的计算有哪些方法	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Word2Vec.md#L164
层次softmax流程	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Word2Vec.md#L164
负采样流程	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Word2Vec.md#L164
word2vec两种方法各自的优势	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Word2Vec.md#L164
怎么衡量学到的embedding的好坏	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Word2Vec.md#L164
word2vec和glove区别	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Word2Vec.md#L164
你觉得word2vec有哪些问题	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Word2Vec.md#L164
阐述CRF原理	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/CRF.md#L164
线性链条件随机场的公式是	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/CRF.md#L164
CRF与HMM区别	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/CRF.md#L164
Bert+crf中的各部分作用详解	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/CRF.md#L164
详述LDA原理	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
LDA中的主题矩阵如何计算	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
LDA的共轭分布解释下	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
PLSA和LDA的区别	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
怎么确定LDA的topic个数	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
LDA和Word2Vec区别？LDA和Doc2Vec区别	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
LDA算法里面Dirichlet分布的两个参数alpha和beta怎样确定？trick?	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
使用过LDA，你有什么问题？	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
你用真实用过吗？对比过效果吗？	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
超参数\alpha \beta对训练的影响？	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
LDA你会有哪些常规的预处理步骤	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
LDA的最大似然不好求的原因？为什么不直接用EM？为什么LDA引入了一堆数学理论？	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/LDA.md#L164
实现/使用的代码	https://github.com/sladesha/deep_learning/tree/master/Bert
Bert的双向体现在什么地方	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
Bert的是怎样预训练的	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
在数据中随机选择 15% 的标记，其中80%被换位[mask]，10%不变、10%随机替换其他单词，原因是什么	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
为什么BERT有3个嵌入层，它们都是如何实现的	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
bert的损失函数	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
手写一个multi-head attention	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
长文本预测如何构造Tokens	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
你用过什么模块？bert流程是怎么样的	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
知道分词模块：FullTokenizer做了哪些事情么	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
Bert中如何获得词意和句意	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
源码中Attention后实际的流程是如何的	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
为什么要在Attention后使用残差结构	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
平时用官方Bert包么？耗时怎么样	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
你觉得BERT比普通LM的新颖点	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
elmo、GPT、bert三者之间有什么区别	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/Bert.md#L164
有哪些常用的方法	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/%E6%96%87%E6%9C%AC%E7%9B%B8%E4%BC%BC%E5%BA%A6%E8%AE%A1%E7%AE%97.md#L164
讲一下textcnn	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/TextCNN.md#L164
textCNN中核的作用	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/TextCNN.md#L164
max-pooling选择的目的	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/TextCNN.md#L164
textcnn和fasttext区别	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/TextCNN.md#L164
如果你知道上面说的核心问题，那么有什么解决方案吗？	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/TextCNN.md#L164
为什么卷积核都不大？且常见都都是奇数？	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/TextCNN.md#L164
为什么不建议用句长作为核大小	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/TextCNN.md#L164
padding是不是对最后结果没有影响	https://github.com/valueable/Reflection_Summary/blob/master/%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86/TextCNN.md#L164
	https://github.com/valueable/Reflection_Summary#推荐
实现/使用的代码	https://github.com/sladesha/deep_learning/tree/master/DeepInterestNetwork
主要使用了什么机制	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DIN.md#L164
activation unit的作用	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DIN.md#L164
DICE怎么设计的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DIN.md#L164
DICE使用的过程中，有什么需要注意的地方	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DIN.md#L164
实现/使用的代码	https://github.com/sladesha/deep_learning/tree/master/DeepFM
DNN与DeepFM之间的区别	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DeepFM.md#L164
Wide&Deep与DeepFM之间的区别	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DeepFM.md#L164
你在使用deepFM的时候是如何处理欠拟合和过拟合问题的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DeepFM.md#L164
DeepFM怎么优化的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DeepFM.md#L164
不定长文本数据如何输入deepFM	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DeepFM.md#L164
deepfm的embedding初始化有什么值得注意的地方吗	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DeepFM.md#L164
Xavier初始化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DeepFM.md#L164
He初始化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/DeepFM.md#L164
实现/使用的代码	https://github.com/sladesha/deep_learning/tree/master/YoutubeNetwork
变长数据如何处理的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
input是怎么构造的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
最后一次点击实际如何处理的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
output的是时候train和predict如何处理的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
如何进行负采样的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
item向量在softmax的时候你们怎么选择的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
Example Age的理解	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
什么叫做不对称的共同浏览（asymmetric co-watch）问题	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
为什么不采取类似RNN的Sequence model	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
YouTube如何避免百万量级的softmax问题的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
serving过程中，YouTube为什么不直接采用训练时的model进行预测，而是采用了一种最近邻搜索的方法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
Youtube的用户对新视频有偏好，那么在模型构建的过程中如何引入这个feature	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
在处理测试集的时候，YouTube为什么不采用经典的随机留一法（random holdout），而是一定要把用户最近的一次观看行为作为测试集	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
整个过程中有什么亮点？有哪些决定性的提升	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/YouTubeNet.md#L164
实现/使用的代码	https://github.com/sladesha/deep_learning/tree/master/XDeepFm/script
选用的原因，考虑使用的场景是什么	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/XDeepFM.md#L164
什么叫显示隐式？什么叫元素级/向量级？什么叫做高阶/低阶特征交互	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/XDeepFM.md#L164
简单介绍一下XDeepFm的思想	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/XDeepFM.md#L164
和DCN比，有哪些核心的变化	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/XDeepFM.md#L164
时间复杂度多少	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/XDeepFM.md#L164
召回层构造loss和精排层的差异？	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/Recall.md#L164
离线评估有什么办法	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/Recall.md#L164
负样本为什么不能用点击未展示	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/Recall.md#L164
解释一下hard negative	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/Recall.md#L164
什么样本是hard和easy的	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/Recall.md#L164
如何处理hard部分	https://github.com/valueable/Reflection_Summary/blob/master/%E6%8E%A8%E8%8D%90/Recall.md#L164
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