Mathematical Introduction to Data Science
Wegner, Sven A.
- 出版商: Springer
- 出版日期: 2024-08-31
- 售價: $3,790
- 貴賓價: 9.5 折 $3,601
- 語言: 英文
- 頁數: 304
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3662694255
- ISBN-13: 9783662694251
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相關分類:
Data Science
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相關主題
商品描述
This textbook is intended for students of mathematics who have completed the foundational courses of their undergraduate studies and now want to specialize in Data Science and Machine Learning. It introduces the reader to the most important topics in the latter areas focusing on rigorous proofs and a systematic understanding of the underlying ideas.
The textbook comes with 121 classroom-tested exercises. Topics covered include k-nearest neighbors, linear and logistic regression, clustering, best-fit subspaces, principal component analysis, dimensionality reduction, collaborative filtering, perceptron, support vector machines, the kernel method, gradient descent and neural networks.
商品描述(中文翻譯)
這本教科書是為已完成本科基礎課程的數學學生所設計,旨在讓他們專注於資料科學和機器學習。它向讀者介紹了這些領域中最重要的主題,重點在於嚴謹的證明和對基本概念的系統理解。
這本教科書包含121個經過課堂測試的練習題。涵蓋的主題包括k-nearest neighbors、線性和邏輯回歸、聚類、最佳擬合子空間、主成分分析、降維、協同過濾、感知器、支持向量機、核方法、梯度下降和神經網絡。
作者簡介
Sven A. Wegner earned his PhD in Functional Analysis in 2010. After several international academic positions, he is currently affiliated with the University of Hamburg (Germany).
作者簡介(中文翻譯)
Sven A. Wegner於2010年獲得功能分析的博士學位。在擔任多個國際學術職位後,他目前隸屬於德國漢堡大學。