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.
##Explain machine learning algorithm with python examples. The description is easy to understand.
評分 評分 評分##Explain machine learning algorithm with python examples. The description is easy to understand.
評分 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。
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