Written in an easily accessible style, this book provides the ideal blend of theory and practical, applicable knowledge. It covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization. It treads the fine line between adequate academic rigor and overwhelming students with equations and mathematical concepts. The author includes examples based on widely available datasets and practical and theoretical problems to test understanding and application of the material. The book describes algorithms with code examples backed up by a website that provides working implementations in Python.
看完这本书之后觉得Machine Learning in Action及其中文版简直太随意了..
评分 评分看完这本书之后觉得Machine Learning in Action及其中文版简直太随意了..
评分 评分 评分##机器学习的算法中很不错的一本书 @2013-04-15 11:14:10 本意拿它来练Python, code: http://seat.massey.ac.nz/personal/s.r.marsland/MLbook.html 优点: 1.对各模型的优缺点有点评 以及 后来的改进稍有介绍; 2.很多Insight 很棒,如此密集给力的Insight,超过任何一本我读过的ML书籍; 3.介绍了部分2000年后的机器学习进展,...
评分 评分##练NumPy。可惜没有完整电子版,图书馆又没有;网上的电子版在后半部分 有很多hidden page。稍带现代气息。
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