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整理记录本人担任课程助教设计的四个机器学习实验,主要涉及简单的线性回归、朴素贝叶斯分类器、支持向量机、CNN做文本分类。内附实验指导书、讲解PPT、参考代码,欢迎各位码友讨论交流。

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ml-experiments's Introduction

ML-Experiments

整理记录本人担任课程助教设计的四个机器学习实验,主要涉及简单的线性回归、朴素贝叶斯分类器、支持向量机、CNN做文本分类。 内附实验指导书、讲解PPT、参考代码,欢迎各位码友讨论交流。  

文件说明

1、实验讲解PPT

  • 实验一 线性回归模型实验指导
  • 实验二 支持向量机模型实验指导
  • 实验三 贝叶斯分类解决西瓜问题
  • 实验四 基于tensorflow实现CNN文本分类

2、实验指导书

  • 实验一 线性回归实验指导书
  • 实验二 支持向量机实验指导书
  • 实验三 贝叶斯分类实验指导书
  • 实验四 基于tensorflow实现cnn文本处理实验指导书

3、实验参考代码

  • 实验一 LinearRegression
  • 实验二 SVM
  • 实验三 bayes_classify_demo
  • 实验四 cnn-text-classification-tf

致谢

  • 感谢学校提供的助教平台,让我能够有机会选择感兴趣的课程,担任助教,提升自我;
  • 感谢导师提供的助教机会,让我可以将所学的机器学习理论知识用于实践;
  • 感谢实验室的同门,帮助我修改实验文档,协助我完成实验答疑。  

注:实验都比较基础,尚有继续提升完善的空间,欢迎大家指教,谢谢。

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