TENSOR CALCULUS for Engineers & Machine Learning: A Step-by-Step Guide with Applications in AI - Physics - Robotics - Optimization
暫譯: 工程師與機器學習的張量微積分：AI - 物理 - 機器人技術 - 優化的逐步指南與應用
Hossain, Mir
- 出版商: Independently Published
- 出版日期: 2026-05-09
- 售價: $1,530
- 貴賓價: 9.5 折 $1,453
- 語言: 英文
- 頁數: 190
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798196277542
- ISBN-13: 9798196277542
-
相關分類:
DeepLearning、工程數學 Engineering-mathematics
無法訂購
商品描述
TENSOR CALCULUS FOR ENGINEERS & MACHINE LEARNING
A Step-by-Step Guide with Applications in AI, Physics, Robotics & Optimization
Struggling to connect the math in physics with the tensors used in deep learning?
This book bridges the gap.
Whether you're an engineering student, machine learning practitioner, or physics learner, Tensor Calculus for Engineers & Machine Learning gives you a clear, practical path to mastering one of the most powerful mathematical tools in modern science.
Instead of treating tensors as abstract theory or just arrays in code, this book shows you how they work across disciplines-using the same notation, the same logic, and real-world applications.
What You'll Learn
- Understand tensors from first principles-without confusion or intimidation
- Master index notation and Einstein summation with ease
- Perform tensor operations used in engineering and AI
- Derive gradients for neural networks, including attention mechanisms
- Apply tensor calculus to mechanics, robotics, and optimization
- Use NumPy, PyTorch, and einsum like a professional
Why This Book Is Different
- Combines engineering + AI applications in every chapter
- Focuses on intuition first, then formal understanding
- Includes 165+ practice problems with full solutions
- Features a complete transformer backpropagation walkthrough
- Designed for real-world problem solving, not memorization
Who This Book Is For
- Engineering students (mechanical, electrical, civil, robotics)
- Machine learning and AI practitioners
- Physics students and applied mathematicians
- Anyone who wants to truly understand tensors-not just use them
Prerequisites
- Basic linear algebra
- Single-variable calculus (multivariable helpful but reviewed inside)
Stop memorizing formulas. Start understanding the language behind modern AI and engineering.
Master tensor calculus-and unlock the mathematics behind today's most powerful technologies.
商品描述(中文翻譯)
**工程師與機器學習的張量微積分**
*AI、物理、機器人學與優化應用的逐步指南*
在物理學中的數學與深度學習中使用的張量之間感到困惑嗎？
這本書填補了這個空白。
無論你是工程學生、機器學習從業者，還是物理學學習者，*工程師與機器學習的張量微積分*都為你提供了一條清晰、實用的道路，幫助你掌握現代科學中最強大的數學工具之一。
這本書不僅將張量視為抽象理論或代碼中的數組，而是展示了它們如何在不同學科中運作——使用相同的符號、相同的邏輯和現實世界的應用。
你將學到的內容
- 從基本原理理解張量——不再困惑或畏懼
- 輕鬆掌握指標符號和愛因斯坦求和
- 執行工程和AI中使用的張量運算
- 為神經網絡推導梯度，包括注意力機制
- 將張量微積分應用於力學、機器人學和優化
- 像專業人士一樣使用NumPy、PyTorch和einsum
這本書的不同之處
- 每一章結合了**工程 + AI 應用**
- 首先專注於**直覺，然後是正式理解**
- 包含**165+ 道練題及完整解答**
- 特別提供**完整的變壓器反向傳播步驟**
- 設計用於**解決現實問題，而非死記公式**
本書適合的人群
- 工程學生（機械、電氣、土木、機器人）
- 機器學習和AI從業者
- 物理學生和應用數學家
- 任何想真正理解張量的人——不僅僅是使用它們
先決條件
- 基本線性代數
- 單變數微積分（多變數微積分有幫助，但書中會進行回顧）
停止死記公式。開始理解現代AI和工程背後的語言。
**掌握張量微積分——解鎖當今最強大技術背後的數學。**
