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.
##终于找到电子版啦!
评分 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。
评分##感觉这本书写得非常基础,但是内容又广,有点高不成,低不就,很多重点内容都没有
评分 评分 评分 评分##终于找到电子版啦!
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