Effective Python

Data stewards in any organization are the backbone of a successful data governance implementation because they do the work to make data trusted, dependable, and high quality. Since the publication of the first edition, there have been critical new developments in the field, such as integrating Data Stewardship into project management, handling Data Stewardship in large international companies, handling "big data" and Data Lakes, and a pivot in the overall thinking around the best way to align data stewardship to the data-moving from business/organizational function to data domain. Furthermore, the role of process in data stewardship is now recognized as key and needed to be covered.Data Stewardship, Second Edition provides clear and concise practical advice on implementing and running data stewardship, including guidelines on how to organize based on organizational/company structure, business functions, and data ownership. The book shows data managers how to gain support for a stewards

本書解釋了scikit-learn API，它是為促進構建機器學習應用程序而創建的軟件包。通過本書的閱讀，讀者將學習如何解釋有監督和無監督模型之間的差異，以及如何將一些流行的算法應用于現實生活中的數據集。首先，本書講解了如何使用scikit-learn的語法。監督和非監督模型之間的差異，以及為每個數據集選擇適當算法的重要性。您將對實際數據集應用無監督聚類算法來發現模式和配置文件，並探索解決無監督機

本書不僅講解了機器學習基本原理和基本方法，而且通過大量醫療領域的案例實現對醫療健康數據的處理和分析，能夠在很大程度上輔助醫護人員進行臨床決策。通過本書學習，讀者不僅能夠掌握機器學習算法建模前的數據準備、篩選構造機器學習算法指標的特徵工程、不同類別的機器學習算法，還能夠掌握臨床診療數據、電子病歷檔案數據及影像數據等多源異構數據的處理方法，以及醫療圖像、文本等數據的讀取、預處理、可視化等知識。同時，本