Linear Algebra: Theory, Intuition, Code (Paperback)

Cohen, Mike X.

Linear Algebra: Theory, Intuition, Code (Paperback)
  • 出版商: Sincxpress Bv
  • 出版日期: 2021-02-01
  • 售價: $1,500
  • 貴賓價: 9.5 折 $1,425
  • 語言: 英文
  • 頁數: 584
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 9083136604
  • ISBN-13: 9789083136608
  • 相關分類: 線性代數 Linear-algebra

    • 立即出貨 (庫存=1)

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商品描述

Linear algebra is perhaps the most important branch of mathematics for computational sciences, including machine learning, AI, data science, statistics, simulations, computer graphics, multivariate analyses, matrix decompositions, signal processing, and so on.
The way linear algebra is presented in traditional textbooks is different from how professionals use linear algebra in computers to solve real-world applications in machine learning, data science, statistics, and signal processing. For example, the "determinant" of a matrix is important for linear algebra theory, but should you actually use the determinant in practical applications? The answer may surprise you
If you are interested in learning the mathematical concepts linear algebra and matrix analysis, but also want to apply those concepts to data analyses on computers (e.g., statistics or signal processing), then this book is for you. You'll see all the math concepts implemented in MATLAB and in Python.

Unique aspects of this book:
- Clear and comprehensible explanations of concepts and theories in linear algebra.
- Several distinct explanations of the same ideas, which is a proven technique for learning.
- Visualization using graphs, which strengthens the geometric intuition of linear algebra.
- Implementations in MATLAB and Python. Com'on, in the real world, you never solve math problems by hand You need to know how to implement math in software
- Beginner to intermediate topics, including vectors, matrix multiplications, least-squares projections, eigendecomposition, and singular-value decomposition.
- Strong focus on modern applications-oriented aspects of linear algebra and matrix analysis.
- Intuitive visual explanations of diagonalization, eigenvalues and eigenvectors, and singular value decomposition.
- Codes (MATLAB and Python) are provided to help you understand and apply linear algebra concepts on computers.
- A combination of hand-solved exercises and more advanced code challenges. Math is not a spectator sport

商品描述(中文翻譯)

線性代數可能是計算科學中最重要的數學分支，包括機器學習、人工智慧、數據科學、統計學、模擬、計算機圖形學、多變量分析、矩陣分解、信號處理等等。

傳統教科書中介紹線性代數的方式與專業人士在計算機中應用線性代數解決機器學習、數據科學、統計學和信號處理等實際應用的方式不同。例如，矩陣的「行列式」在線性代數理論中很重要，但在實際應用中是否應該使用行列式呢？答案可能會讓你驚訝。

如果你有興趣學習線性代數和矩陣分析的數學概念，同時也想將這些概念應用於計算機上的數據分析（例如統計學或信號處理），那麼這本書就是為你而寫的。你將看到所有數學概念在MATLAB和Python中的實現。

本書的獨特之處包括：
- 清晰易懂地解釋線性代數的概念和理論。
- 對同一概念提供多種不同的解釋，這是一種學習的有效技巧。
- 使用圖形進行可視化，增強對線性代數的幾何直觀理解。
- 在MATLAB和Python中實現。在現實世界中，你不會手動解決數學問題，你需要知道如何在軟件中實現數學。
- 從初級到中級的主題，包括向量、矩陣乘法、最小二乘投影、特徵分解和奇異值分解。
- 強調線性代數和矩陣分析的現代應用導向方面。
- 直觀的視覺解釋對角化、特徵值和特徵向量以及奇異值分解。
- 提供代碼（MATLAB和Python）以幫助你理解和應用計算機上的線性代數概念。
- 結合手動解決的練習和更高級的代碼挑戰。數學不是一場觀賞比賽。

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