Data Science and Analytics with Python (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data science using tools developed in Python, such as SciKit-learn, Pandas, Numpy, and others. The use of Python is of particular interest, given its recent popularity in the data science community. The book can be used by seasoned programmers and newcomers alike.

The book is organized in a way that individual chapters are sufficiently independent from each other so that the reader is comfortable using the contents as a reference. The book discusses what data science and analytics are, from the point of view of the process and results obtained. Important features of Python are also covered, including a Python primer. The basic elements of machine learning, pattern recognition, and artificial intelligence that underpin the algorithms and implementations used in the rest of the book also appear in the first part of the book.

Regression analysis using Python, clustering techniques, and classification algorithms are covered in the second part of the book. Hierarchical clustering, decision trees, and ensemble techniques are also explored, along with dimensionality reduction techniques and recommendation systems. The support vector machine algorithm and the Kernel trick are discussed in the last part of the book.

About the Author

Dr. Jesús Rogel-Salazar is a Lead Data scientist with experience in the field working for companies such as AKQA, IBM Data Science Studio, Dow Jones and others. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK, He obtained his doctorate in physics at Imperial College London for work on quantum atom optics and ultra-cold matter. He has held a position as senior lecturer in mathematics as well as a consultant in the financial industry since 2006. He is the author of the book Essential Matlab and Octave, also published by CRC Press. His interests include mathematical modelling, data science, and optimization in a wide range of applications including optics, quantum mechanics, data journalism, and finance.

《使用Python進行數據科學與分析》是專為學術和商業環境中的數據科學和數據分析從業人員設計的。其目的是通過使用Python開發的工具（如SciKit-learn、Pandas、Numpy等）向讀者介紹數據科學中使用的主要概念。考慮到Python在數據科學社區中的近期流行，使用Python對讀者來說尤其有趣。這本書適用於有經驗的程序員和新手。

本書的組織方式使得各個章節相互獨立，讀者可以將其內容作為參考使用。本書從過程和結果的角度討論了數據科學和數據分析的概念。同時也介紹了Python的重要特性，包括Python入門知識。機器學習、模式識別和人工智能的基本元素是本書的第一部分，這些元素是本書其餘部分中使用的算法和實現的基礎。

本書的第二部分介紹了使用Python進行回歸分析、聚類技術和分類算法。同時還探討了層次聚類、決策樹和集成技術，以及降維技術和推薦系統。支持向量機算法和核技巧則在本書的最後一部分進行了討論。

關於作者：
Dr. Jesús Rogel-Salazar是一位領先的數據科學家，曾在AKQA、IBM數據科學工作室、道瓊斯等公司工作。他是英國倫敦帝國學院物理系的訪問研究員，也是英國赫特福德郡大學物理、天文和數學學院的成員。他在倫敦帝國學院獲得了物理學博士學位，研究領域是量子原子光學和超冷物質。自2006年以來，他一直擔任數學高級講師和金融行業顧問。他還是CRC Press出版的《Essential Matlab and Octave》一書的作者。他的興趣包括數學建模、數據科學和優化，涵蓋了光學、量子力學、數據新聞和金融等廣泛應用領域。