Fundamentals of Supervised Machine Learning: With Applications in Python, R, and Stata (監督式機器學習基礎:以 Python、R 和 Stata 的應用為例)

Cerulli, Giovanni

  • 出版商: Springer
  • 出版日期: 2024-11-15
  • 售價: $3,740
  • 貴賓價: 9.5$3,553
  • 語言: 英文
  • 頁數: 391
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3031413393
  • ISBN-13: 9783031413391
  • 相關分類: Python程式語言Machine Learning
  • 海外代購書籍(需單獨結帳)

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商品描述

This book presents the fundamental theoretical notions of supervised machine learning along with a wide range of applications using Python, R, and Stata. It provides a balance between theory and applications and fosters an understanding and awareness of the availability of machine learning methods over different software platforms.

After introducing the machine learning basics, the focus turns to a broad spectrum of topics: model selection and regularization, discriminant analysis, nearest neighbors, support vector machines, tree modeling, artificial neural networks, deep learning, and sentiment analysis. Each chapter is self-contained and comprises an initial theoretical part, where the basics of the methodologies are explained, followed by an applicative part, where the methods are applied to real-world datasets. Numerous examples are included and, for ease of reproducibility, the Python, R, and Stata codes used in the text, along with the related datasets, are available online.

The intended audience is PhD students, researchers and practitioners from various disciplines, including economics and other social sciences, medicine and epidemiology, who have a good understanding of basic statistics and a working knowledge of statistical software, and who want to apply machine learning methods in their work.


商品描述(中文翻譯)

本書介紹了監督式機器學習的基本理論概念,以及使用 Python、R 和 Stata 的廣泛應用。它在理論與應用之間取得平衡,並促進對不同軟體平台上機器學習方法可用性的理解與認識。

在介紹機器學習基礎知識後,重點轉向廣泛的主題範疇:模型選擇與正則化、判別分析、最近鄰、支持向量機、樹模型、人工神經網絡、深度學習和情感分析。每一章都是獨立的,包含初步的理論部分,解釋方法論的基本概念,接著是應用部分,將這些方法應用於真實世界的數據集。書中包含了許多範例,為了方便重現,文中使用的 Python、R 和 Stata 代碼以及相關數據集均可在線獲得。

本書的目標讀者為博士生、研究人員及來自各個學科的實務工作者,包括經濟學及其他社會科學、醫學和流行病學等,這些讀者需具備良好的基本統計知識和統計軟體的實務操作能力,並希望在其工作中應用機器學習方法。

作者簡介

Dr. Giovanni Cerulli is a Senior Researcher at the CNR-IRCrES, Research Institute on Sustainable Economic Growth, National Research Council of Italy in Rome. His research interests are in applied econometrics, with a special focus on causal inference and machine learning. He has developed original causal inference models, such as dose-response and treatment models with social interaction, and has carried out many Stata commands for causal inference and machine learning. He has published articles in several high-quality scientific journals, and a book: Econometric Evaluation of Socio-Economic Programs: Theory and Applications. He is currently the Editor-in-Chief of The International Journal of Computational Economics and Econometrics.


作者簡介(中文翻譯)

Dr. Giovanni Cerulli 是義大利國家研究院 CNR-IRCrES(可持續經濟增長研究所)的高級研究員。他的研究興趣集中在應用計量經濟學,特別是因果推斷和機器學習。他開發了原創的因果推斷模型,如劑量反應模型和具有社會互動的處理模型,並執行了許多用於因果推斷和機器學習的 Stata 命令。他在多本高品質科學期刊上發表了文章,並出版了一本書:《社會經濟計畫的計量經濟學評估:理論與應用》。他目前是《國際計算經濟學與計量經濟學期刊》的主編。