“第十四章 学习策略”版本间的差异
来自cslt Wiki
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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:// | + | * 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:// | + | * AI100问：什么是贝叶斯网络 [http://aigraph.cslt.org/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:// | + | * AI100问：什么是人工神经网络[http://aigraph.cslt.org/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:// | + | * AI100问：什么是遗传算法[http://aigraph.cslt.org/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] | ||
| − | * 维基百科：符号主义[http://aigraph.cslt.org/courses/ | + | * 维基百科：符号主义[http://aigraph.cslt.org/courses/14/符號人工智能.pdf][http://aigraph.cslt.org/courses/14/Symbolic_artificial_intelligence.pdf] |
| − | * 维基百科：贝叶斯网络 [http://aigraph.cslt.org/courses/ | + | * 维基百科：贝叶斯网络 [http://aigraph.cslt.org/courses/14/貝氏網路.pdf][http://aigraph.cslt.org/courses/14/Bayesian_network.pdf] |
| − | * 维基百科：神经网络 [http://aigraph.cslt.org/courses/ | + | * 维基百科：神经网络 [http://aigraph.cslt.org/courses/14/人工神经网络.pdf][http://aigraph.cslt.org/courses/14/Artificial_neural_network.pdf] |
| − | * 维基百科：演化学习 [http://aigraph.cslt.org/courses/ | + | * 维基百科：演化学习 [http://aigraph.cslt.org/courses/14/Evolutionary_algorithm.pdf][http://aigraph.cslt.org/courses/14/遗传算法.pdf][http://aigraph.cslt.org/courses/14/Genetic_algorithm.pdf] |
==视频展示== | ==视频展示== | ||
| − | * Genetic Algorithm Explanation [http://aigraph.cslt.org/courses/ | + | * Genetic Algorithm Explanation [http://aigraph.cslt.org/courses/14/GA_Explanation.mp4] |
| 第33行： | 第33行： | ||
* 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] | + | * 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) 01:27的最后版本
教学资料
扩展阅读
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]
