Classical Machine Learning: A Practical Guide Using Python
暫譯: 經典機器學習：使用 Python 的實用指南

Aburass, Sanad, Aljarah, Ibrahim

Classical Machine Learning: A Practical Guide Using Python
  • 出版商: Springer
  • 出版日期: 2026-07-31
  • 售價: $3,670
  • 貴賓價: 9.5 折 $3,486
  • 語言: 英文
  • 頁數: 312
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3032043980
  • ISBN-13: 9783032043986
  • 相關分類: Machine Learning、Python

    • 海外代購書籍(需單獨結帳)

商品描述

The field of Artificial Intelligence (AI) has rapidly transformed in recent years, with Machine Learning being now one of its most impactful and widely applied branches. From intelligent recommendation systems to self-driving cars, and from language translation to medical diagnosis, Machine Learning now touches nearly every aspect of modern life. Yet, for those beginning their journey into AI, the field can feel daunting--particularly with the increasing complexity of deep learning and generative models. In the midst of this fast-paced evolution, it is easy to overlook the foundational ideas that make these breakthroughs possible.

This book is written to bridge this gap and was born from the belief that a solid understanding of classical machine learning is not just helpful, but essential for truly grasping the advanced and modern models shaping today's AI landscape. The authors' goal is to explain classical models clearly and intuitively, while also providing hands-on Python implementations that bring these models to life and offering, as such, a balanced practical approach.

The authors cover a wide range of foundational topics, from linear regression and logistic regression to decision trees, ensemble methods, clustering, dimensionality reduction, neural networks, and convolutional operations. Emerging ideas like Cubixel representation in image processing are also presented, providing a forward-looking perspective on evolving practices. Each chapter builds on the last, combining theory, math, and code in a way that is accessible to students, researchers, and professionals alike.

The book assumes a working knowledge of Linear Algebra and Calculus, as many algorithms rely on these mathematical underpinnings. A solid foundation in Python is also recommended, since practical examples and implementations are written in Python with widely used libraries such as NumPy, pandas, scikit-learn, and TensorFlow. Whether you're an aspiring machine learning engineer, a data scientist transitioning from another field, or an academic looking to refresh your knowledge, this book aims to be a practical companion on your learning journey.

商品描述(中文翻譯)

人工智慧（AI）領域在近年來迅速轉變，其中機器學習已成為其最具影響力和廣泛應用的分支之一。從智能推薦系統到自駕車，從語言翻譯到醫療診斷，機器學習如今幾乎觸及現代生活的每一個方面。然而，對於剛開始進入AI領域的人來說，這個領域可能會感到令人畏懼，尤其是隨著深度學習和生成模型的複雜性不斷增加。在這種快速演變的過程中，容易忽視使這些突破成為可能的基礎概念。

本書旨在填補這一空白，源於這樣的信念：對於真正理解塑造當今AI格局的先進和現代模型，扎實的古典機器學習知識不僅有幫助，更是必不可少。作者的目標是清晰且直觀地解釋古典模型，同時提供實作的Python範例，讓這些模型生動呈現，並因此提供一種平衡的實用方法。

作者涵蓋了廣泛的基礎主題，從線性回歸和邏輯回歸到決策樹、集成方法、聚類、降維、神經網絡和卷積運算。新興的概念如圖像處理中的Cubixel表示法也被介紹，提供對不斷演變的實踐的前瞻性視角。每一章都在前一章的基礎上構建，將理論、數學和程式碼結合在一起，以便於學生、研究人員和專業人士理解。

本書假設讀者具備線性代數和微積分的基本知識，因為許多算法依賴於這些數學基礎。也建議具備扎實的Python基礎，因為實際範例和實作是用Python編寫，並使用了如NumPy、pandas、scikit-learn和TensorFlow等廣泛使用的庫。無論你是有志成為機器學習工程師的初學者、從其他領域轉型的數據科學家，還是希望刷新知識的學者，本書旨在成為你學習旅程中的實用夥伴。

作者簡介

Sanad Aburass is an Assistant Professor of Computer Science at Luther College in Iowa, USA. He holds a Ph.D. in Computer Science from the University of Jordan, specializing in Machine Learning and Computer Vision. Dr. Aburass teaches a range of courses in machine learning, algorithms, data science, web programming and object-oriented programming, emphasizing real-world application and student-centered learning. He is an active researcher with numerous publications in top-tier journals and conferences, and he serves as a guest editor for a Research Topic at Frontiers in Medicine. He also holds a registered patent in Germany for a social media-based targeted marketing framework. In addition to his research in machine learning and computer vision, Dr. Aburass has presented widely on philosophical topics at academic conferences and has published several works in this field. He regularly contributes articles to the Jordanian newspaper Addustour, addressing themes in philosophy, psychology, society, and technology. His book United Martians: A Trip to the Future explores philosophical, psychological, and sociological ideas aimed at fostering a more harmonious and united society.

Ibrahim Aljarah is currently a Professor of Artificial Intelligence at the University of Jordan, Amman, Jordan, as well as a Chief AI Officer and executive consultant at Arrowad Group and Kaizen Consulting, where he leads initiatives and strategies related to artificial intelligence, driving innovation and technological advancement within the organization and its clients. He is a distinguished researcher, recognized globally for his expertise in artificial intelligence, data mining, and big data. He is also a Highly Cited Researcher (Clarivate Analytics) and a Senior Member of IEEE (SMIEEE), with numerous publications ranked in the top 1% by citations according to Web of Science. He earned his Ph.D. in Computer Science from North Dakota State University in 2014 and served as Head of the AI Department at the University of Jordan in 2022. From 2019 to 2025, he has been among the university's top publishing researchers, with over 140 high-impact publications, 3 books, more than 20,200 citations, and an h-index of 60. Prof. Aljarah has received several prestigious awards, including the UJ Distinguished Researcher Award (2022) and the Ali Mango Award (2020). He ranks among the top 2% of scientists worldwide and among the top 10 in Jordan in AI and image processing, according to Stanford University (2020-2025). He has presented at major international conferences and contributed to key projects in the U.S., such as the Vehicle Class Detection System and PAVVET. His research interests span machine learning, swarm intelligence, evolutionary computation, and big data technologies.

作者簡介(中文翻譯)

Sanad Aburass 是美國愛荷華州路德學院的計算機科學助理教授。他擁有約旦大學的計算機科學博士學位，專攻機器學習和計算機視覺。Aburass 博士教授一系列課程，包括機器學習、演算法、數據科學、網頁程式設計和物件導向程式設計，強調實際應用和以學生為中心的學習。他是一位活躍的研究者，在頂尖期刊和會議上發表了多篇論文，並擔任《Frontiers in Medicine》的研究主題特約編輯。他在德國擁有一項針對社交媒體的目標行銷框架的註冊專利。除了在機器學習和計算機視覺方面的研究外，Aburass 博士還在學術會議上廣泛發表有關哲學主題的演講，並在該領域發表了幾部作品。他定期為約旦報紙《Addustour》撰寫文章，探討哲學、心理學、社會和技術等主題。他的書籍《United Martians: A Trip to the Future》探討了旨在促進更和諧和團結社會的哲學、心理學和社會學思想。

Ibrahim Aljarah 目前是約旦安曼約旦大學的人工智慧教授，同時擔任 Arrowad Group 和 Kaizen Consulting 的首席人工智慧官及執行顧問，負責推動與人工智慧相關的倡議和策略，促進組織及其客戶的創新和技術進步。他是一位傑出的研究者，因其在人工智慧、數據挖掘和大數據方面的專業知識而在全球受到認可。他也是一位高被引研究者（Clarivate Analytics）和 IEEE 高級會員（SMIEEE），在 Web of Science 上有多篇論文的引用排名位於前 1%。他於 2014 年在北達科他州立大學獲得計算機科學博士學位，並於 2022 年擔任約旦大學人工智慧系主任。從 2019 年到 2025 年，他一直是該大學的頂尖發表研究者之一，擁有超過 140 篇高影響力的出版物、3 本書籍、超過 20,200 次引用和 60 的 h-index。Aljarah 教授獲得了多項著名獎項，包括 UJ 傑出研究者獎（2022）和 Ali Mango 獎（2020）。根據史丹佛大學（2020-2025）的資料，他在全球科學家中排名前 2%，在約旦的人工智慧和影像處理領域排名前 10%。他曾在主要國際會議上發表演講，並參與美國的關鍵項目，如車輛類別檢測系統和 PAVVET。他的研究興趣涵蓋機器學習、群體智慧、演化計算和大數據技術。

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