TENSOR CALCULUS for Engineers & Machine Learning: A Step-by-Step Guide with Applications in AI · Physics · Robotics · Optimization

By: Mir Hossain

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 LearnUnderstand tensors from first principles-without confusion or intimidationMaster index notation and Einstein summation with easePerform tensor operations used in engineering and AIDerive gradients for neural networks, including attention mechanismsApply tensor calculus to mechanics, robotics, and optimizationUse NumPy, PyTorch, and einsum like a professional
Why This Book Is DifferentCombines engineering + AI applications in every chapterFocuses on intuition first, then formal understandingIncludes 165+ practice problems with full solutionsFeatures a complete transformer backpropagation walkthroughDesigned for real-world problem solving, not memorization
Who This Book Is ForEngineering students (mechanical, electrical, civil, robotics)Machine learning and AI practitionersPhysics students and applied mathematiciansAnyone who wants to truly understand tensors-not just use them
PrerequisitesBasic linear algebraSingle-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.

• Format: Paperback
• Language: English
• ISBN: B0H17YH99X
• ISBN13: 9798196277542
• Release Date: May 2026
• Publisher: Independently published
• Length: 189 Pages
• Weight: 0.75 lbs.
• Dimensions: 10.0" x 0.4" x 7.0"