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.
##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 評分##從算法的角度學習ml,代碼很有學習價值。
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..
評分 評分 評分##機器學習的算法中很不錯的一本書 @2013-04-15 11:14:10 本意拿它來練Python, code: http://seat.massey.ac.nz/personal/s.r.marsland/MLbook.html 優點: 1.對各模型的優缺點有點評 以及 後來的改進稍有介紹; 2.很多Insight 很棒,如此密集給力的Insight,超過任何一本我讀過的ML書籍; 3.介紹瞭部分2000年後的機器學習進展,...
評分##練NumPy。可惜沒有完整電子版,圖書館又沒有;網上的電子版在後半部分 有很多hidden page。稍帶現代氣息。
評分##Explain machine learning algorithm with python examples. The description is easy to understand.
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