“第十四章 学习策略”版本间的差异

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==扩展阅读==
 
==扩展阅读==
  
* AI100问:机器学习有哪些基本方法[http://166.111.134.44:7777/caiyq/ai100/pdf/AI-100-34-%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E6%9C%89%E5%93%AA%E4%BA%9B%E4%B8%BB%E8%A6%81%E6%96%B9%E6%B3%95.pdf]
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* AI100问:机器学习有哪些基本方法[http://aigraph.cslt.org/ai100/pdf/AI-100-34-%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E6%9C%89%E5%93%AA%E4%BA%9B%E4%B8%BB%E8%A6%81%E6%96%B9%E6%B3%95.pdf]
* AI100问:什么是贝叶斯网络 [http://166.111.134.44:7777/caiyq/ai100/pdf/AI-100-49-%E4%BB%80%E4%B9%88%E6%98%AF%E8%B4%9D%E5%8F%B6%E6%96%AF%E7%BD%91%E7%BB%9C.pdf]
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* AI100问:什么是贝叶斯网络 [http://aigraph.cslt/ai100/pdf/AI-100-49-%E4%BB%80%E4%B9%88%E6%98%AF%E8%B4%9D%E5%8F%B6%E6%96%AF%E7%BD%91%E7%BB%9C.pdf]
* AI100问:什么是人工神经网络[http://166.111.134.44:7777/caiyq/ai100/pdf/AI-100-47-%E4%BB%80%E4%B9%88%E6%98%AF%E4%BA%BA%E5%B7%A5%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C.pdf]
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* AI100问:什么是人工神经网络[http://aigraph.cslt/ai100/pdf/AI-100-47-%E4%BB%80%E4%B9%88%E6%98%AF%E4%BA%BA%E5%B7%A5%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C.pdf]
* AI100问:什么是遗传算法[http://166.111.134.44:7777/caiyq/ai100/pdf/AI-100-25-%E4%BB%80%E4%B9%88%E6%98%AF%E9%81%97%E4%BC%A0%E7%AE%97%E6%B3%95.pdf]
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* AI100问:什么是遗传算法[http://aigraph.cslt/ai100/pdf/AI-100-25-%E4%BB%80%E4%B9%88%E6%98%AF%E9%81%97%E4%BC%A0%E7%AE%97%E6%B3%95.pdf]
  
 
* 百度百科:符号主义[https://baike.baidu.com/item/%E7%AC%A6%E5%8F%B7%E4%B8%BB%E4%B9%89/10570834]
 
* 百度百科:符号主义[https://baike.baidu.com/item/%E7%AC%A6%E5%8F%B7%E4%B8%BB%E4%B9%89/10570834]
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* Python package for rule induction: Rule kit [https://github.com/adaa-polsl/RuleKit-python] imodels[https://libraries.io/pypi/imodels]
 
* Python package for rule induction: Rule kit [https://github.com/adaa-polsl/RuleKit-python] imodels[https://libraries.io/pypi/imodels]
 
* Python package for neural nets: PyTorch [https://pytorch.org/] TensorFlow[https://www.tensorflow.org/learn] NeuralLab[https://github.com/zueve/neurolab]
 
* Python package for neural nets: PyTorch [https://pytorch.org/] TensorFlow[https://www.tensorflow.org/learn] NeuralLab[https://github.com/zueve/neurolab]
* Python package for Bayes network: bnlearn[https://pypi.org/project/bnlearn/]pgmpy[https://pgmpy.org/index.html]pomegranate [https://pomegranate.readthedocs.io/en/latest/index.html]  
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* Python package for Bayes network: bnlearn[https://pypi.org/project/bnlearn/]pgmpy[https://pgmpy.org/index.html]pomegranate [https://pomegranate.readthedocs.io/en/latest/index.html]
 
* Python package for evolutionary learning: PyGAD[https://pygad.readthedocs.io/en/latest/] geneticalgorithm2 [https://pypi.org/project/geneticalgorithm2/] GeneAI[https://github.com/diogomatoschaves/geneal]
 
* Python package for evolutionary learning: PyGAD[https://pygad.readthedocs.io/en/latest/] geneticalgorithm2 [https://pypi.org/project/geneticalgorithm2/] GeneAI[https://github.com/diogomatoschaves/geneal]
  

2023年8月13日 (日) 01:23的版本

教学资料

  • 教学参考
  • 课件
  • 小清爱提问:机器学习有哪些基本方法?[1]
  • 小清爱提问:什么是遗传算法?[2]

扩展阅读

  • AI100问:机器学习有哪些基本方法[3]
  • AI100问:什么是贝叶斯网络 [4]
  • AI100问:什么是人工神经网络[5]
  • AI100问:什么是遗传算法[6]


视频展示

  • Genetic Algorithm Explanation [17]


演示链接


开发者资源

  • Python package for rule induction: Rule kit [21] imodels[22]
  • Python package for neural nets: PyTorch [23] TensorFlow[24] NeuralLab[25]
  • Python package for Bayes network: bnlearn[26]pgmpy[27]pomegranate [28]
  • Python package for evolutionary learning: PyGAD[29] geneticalgorithm2 [30] GeneAI[31]


高级读者

  • Bayes demo[32]
  • Cranmer et al., Discovering Symbolic Models from Deep Learning with Inductive Biases [33]
  • 王东,机器学习导论,2021,清华大学出版社 [34]
  • Pedro Domingos' Master Algorithm: How machine learning is reshaping how we live". Slate.com. Retrieved September 26, 2015 [35]