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cs188's Introduction

2022 级中山大学人工智能学院 人工智能原理实验课作业

授课老师:彭振辉

参考 CS188 UCBerkeley Fall2018 课程内容

理论习题 Gradescope

学校选择UC berkely,课程注册码为:93PWD8

上课课件

所有课程课件存储在课件文件夹中


参考资料

课程note

由知乎好心用户经过教授授权后翻译

  1. 课程 note-1
  2. 课程 note-2
  3. 课程 note-3
  4. 课程 note-4
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  1. 爬山法
  2. 模拟退火
  3. 遗传算法
UCB
  1. UCB 算法
  2. UCB 案例+代码
MiniMax
  1. alpha-beta 详细推导和讲解
MDP-markov-decision-process
  1. MDP 笔记总结

  2. Markov decision process MDP 基础概念介绍和代码示例

  3. MDP: Value Iteration

  4. MDP: Value Iteration with code implementation

  5. MDP: policy iteration with code implementation

  6. 关于 project3 task4 中 Prioritized Sweeping Value Iteration 算法的介绍

RL-强化学习
  1. note10 - Exploration and Exploitation
  2. note11 - Reinforcement Learning
  3. model-based ADP learner with code implementation
  4. Model-free MC learner with code implementation -- Monte Carlo 蒙特卡洛
  5. Reinforcement learning: concepts of Q-learning
  6. Reinforcement learning: Q-learner with detailed example and code implementation
Machine Learning
  1. RNN 详解
  2. Note 21: Linear Regression and Perceptron
  3. Note 22: Logistic Regression and Multi-Class Logistic Regression
  4. Note 23: Optimizer
  5. Note 24: Neural Networks overview
Bayes Net and HMM
  1. HMM
  2. VE-1: vairable elimination -- 斯坦福大学 cs288note,思路与课件一致,归纳总结的很棒,但更多的是直觉上的阐述
  3. VE-2: vairable elimination -- 给出了代码示例和详尽的例子
  4. 判断贝叶斯网络中变量是否独立
  5. 机器学习-白板推导系列-隐马尔可夫模型

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