Data Science and Analytics with Python (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)
暫譯: 使用 Python 的資料科學與分析(Chapman & Hall/CRC 資料挖掘與知識發現系列)
Jesus Rogel-Salazar
- 出版商: Chapman and Hall/CRC
- 出版日期: 2017-12-26
- 售價: $5,180
- 貴賓價: 9.5 折 $4,921
- 語言: 英文
- 頁數: 400
- 裝訂: Hardcover
- ISBN: 1138043176
- ISBN-13: 9781138043176
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相關分類:
Python、程式語言、Data-mining、Data Science
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相關主題
商品描述
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.商品描述(中文翻譯)
《使用 Python 的資料科學與分析》旨在為學術和商業環境中的資料科學和資料分析從業者提供指導。其目的是向讀者介紹資料科學中使用的主要概念,並使用 Python 開發的工具,如 SciKit-learn、Pandas、Numpy 等。考慮到 Python 在資料科學社群中的近期流行,使用 Python 特別引人注目。本書適合經驗豐富的程式設計師和新手使用。
本書的組織方式使得各章節之間相對獨立,讀者可以輕鬆地將內容作為參考。書中討論了資料科學和分析的定義,從過程和結果的角度進行探討。重要的 Python 特性也被涵蓋,包括 Python 入門。機器學習、模式識別和人工智慧的基本元素,這些元素支撐著本書其餘部分中使用的演算法和實作,也出現在書的前半部分。
本書的第二部分涵蓋了使用 Python 的迴歸分析、聚類技術和分類演算法。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。支持向量機演算法和核技巧則在本書的最後部分進行討論。
關於作者
耶穌·羅赫爾-薩拉薩博士是首席資料科學家,擁有在 AKQA、IBM 資料科學工作室、道瓊斯等公司的工作經驗。他是英國倫敦帝國學院物理系的訪問研究員,也是英國哈特福德郡大學物理、天文學和數學學院的成員。他在倫敦帝國學院獲得物理學博士學位,研究主題為量子原子光學和超冷物質。自 2006 年以來,他擔任數學高級講師及金融行業顧問。他是書籍《Essential Matlab and Octave》的作者,該書同樣由 CRC Press 出版。他的興趣包括數學建模、資料科學和在光學、量子力學、資料新聞學和金融等廣泛應用中的優化。