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.
##從算法的角度學習ml,代碼很有學習價值。
評分##感覺這本書寫得非常基礎,但是內容又廣,有點高不成,低不就,很多重點內容都沒有
評分##Explain machine learning algorithm with python examples. The description is easy to understand.
評分##終於找到電子版啦!
評分##從算法的角度學習ml,代碼很有學習價值。
評分 評分 評分看完這本書之後覺得Machine Learning in Action及其中文版簡直太隨意瞭..
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