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Unclear issue

by hzq

1. 深度学习相比浅层学习的优势，是如何解决梯度消失的
2. 深度网络的损失如何度量以及如何训练
3. 卷积、池化、dropout的原理
4. 深度网络防止过拟合的方式
5. 构造深度网络输入的一些技巧及其作用原理
6. 如何理解RNN的记忆特性
7. 数据量及数据（包括标签）干净程度对深度网络的影响。

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Book list

1. 机器学习
2. Deep Learning
3. understanding machine learning
4. machine learning yearning
5. 神经网络与机器学习(第三版)
6. 神经网络与深度学习 讲义

project idea

1. 口形识别，输入口型输出普通话
2. 步态识别，通过步态，确定一个人
3. 异常行为检测，打人检测、丢弃物品之类的
4. 人脸识别较为成熟，但是也可以从头到尾走一遍

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