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A Chinese learning note with python codes for Pattern Recognition and Machine Learning.

Pattern-Recognition-and-Machine-Learning中文读书笔记

在阅读机器学习与模式识别时的读书笔记，PRML中文版可以看马春鹏博士翻译的，专业术语准确，概念通俗易懂。这本书对数学要求的不算很高，理工科学生看懂无压力。 笔记以书中重要概念和公式推导为基础，大部分算法都用python简单实现了一遍。书中第5章神经网络，第8章图模型没有笔记，神经网络作为深度学习基础，有很多教程， 推荐吴恩达教授的deeplearning.ai课程。

  1. Introduction
  2. Probability-Distributions
  3. Linear-Models-for-Regression
  4. Linear-Models-for-Classification
  5. Neural-Network
  6. Kernel-Methods
  7. Sparse-Kernel-Machine
  8. Graph-Model
  9. Mixture-Models-and-EM
  10. Approximate-Inference
  11. Sampling
  12. Continuous-Latent-Variables

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A Chinese learning note with python codes for Pattern Recognition and Machine Learning.

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