October 2017
Intermediate to advanced
384 pages
7h 29m
Chinese
Overview
資料科學的學習指引
“對任何想要使用Python開始機器學習的人，這本書是很棒且超實用的資源。真希望當我開始使用scikit-learn時有這本書！”
-Hanna Wallach, 微軟研究院資深研究員
機器學習已成為許多商業應用程式與研究專案的精華部分，但這個領域並不是大公司中規模龐大的研究團隊所獨有。就算是使用Python的初學者，這本書也能教會你實際的方法，來建立自己的機器學習解決方案。以現今可以取得的資料量來說，只要你能想到的，機器學習應用程式都能做到。
你將學習必要的步驟，使用Python和scikit-learn函式庫，來建立成功的機器學習應用程式。作者Andreas Müller和Sarah Guido聚焦於使用機器學習演算法的實務面向，而不是它們背後的數學。熟悉NumPy和matplotlib函式庫，將幫助你能從這本書獲益更多。
透過這本書，你將學到：
‧基本概念和機器學習應用程式
‧廣泛應用機器學習演算法的優點和缺點
‧使用機器學習如何重現資料，包含資料的重點面向
‧模型評估的進階方法和參數調整
‧對鏈結模型的pipeline概念和封裝工作流程
‧運作文字資料的方法，包含特定文字的處理技術
‧對改善機器學習和資料科學技巧的建議
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