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《神经网络与深度学习》课程练习

书籍信息:神经网络与深度学习

欢迎大家补充练习题目。

环境设定

本次作业需要首先安装 anaconda3 下载地址 https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/ , tensorflow 2.0 pytorch >0.4

Exercise

1. 热身练习 warmup

numpy是Python中对于矩阵处理很实用的工具包,本小节作业主要是熟悉基本的numpy操作。

2. 线性回归模型 Linear Regression

3. 线性模型

  1. 支持向量机 support vector machine
  2. Softmax回归 Softmax Regression

4. 前馈神经网络 Simple Neural Network

利用numpy实现全连接神经网络

5. 卷积神经网络 Convolutional Neural Network (CNN)

利用卷积神经网络,处理MNIST 数据集分类问题。

6. 循环神经网络 Recurrent Neural Network (RNN)

基于循环神经网络的唐诗生成问题

7. 注意力机制 Attention Mechanism

  1. 使用sequence to sequence 模型将一个字符串序列逆置。
  2. 使用attentive sequence to sequence 模型将一个字符串序列逆置。

11. 高斯混合模型 Gaussian Mixture Model

12. 受限玻尔兹曼机 Restricted Boltzmann Machine (RBM)

使用受限玻尔兹曼机(Restricted Boltzmann Machine, RBM),对MNIST 数据集建模。

14. 深度强化学习 Deep Reinforcement Learning

强化学习: 黑白棋

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