Description: The book mainly covers the current variety of the most practical machine learning theory and algorithms, including the concept of learning, decision trees, neural networks, Bayesian learning, instance-based learning, genetic algorithms, rule learning, explanation-based learning and enhance learning
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决策树学习.ppt
评估假设.ppt
人工神经网络.ppt
学习规则集合.ppt
遗传算法.ppt
机器学习引言.ppt
增强学习.ppt
贝叶斯学习.ppt
分析学习.ppt
归纳和分析学习的结合.ppt
基于符号和逻辑表示的概念学习.ppt
基于实例的学习.ppt
计算学习理论.ppt
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