Notes for Computational Linear Algebra by Jessy Grizzle
Notes for Computational Linear Algebra - Table of Contents
1. Introduction to Systems of Linear Equations
2. Vectors, Matrices, and Determinants
3. Triangular Systems of Equations: Forward and Back Substitution
4. Matrix Multiplication
5. LU (Lower-Upper) Factorization
6. Determinant of a Product, Matrix Inverses, and the Matrix Transpose
7. The Vector Space Rn: Part 1
8. Euclidean Norm, Least Squared Error Solutions to Linear Equations, and Linear Regression
9. The Vector Space Rn: Part 2
10. Changing Gears: Solutions of Nonlinear Equations
11. Changing Gears Again: Basic Ideas of Optimization
A. Background for Machine Learning
B. To Learn on Your Own (if you want to): Cool and Important Things We Omitted From our Linear Algebra Introduction
C. What is an Ordinary Differential Equation?
D. Camera and LiDAR Models for Students of Robotics
What You Will Learn in Notes for Computational Linear Algebra
"ROB 101 Computational Linear Algebra: Mathematics at the Scale of Life" by Jessy Grizzle is a practical and student-friendly introduction to linear algebra, written specifically for applications in engineering and robotics. The book avoids heavy abstraction and instead focuses on building intuition through "computational thinking" and real problem solving. It is widely used in introductory robotics and engineering courses.
The notes emphasize how linear algebra is used in practice, covering topics such as "linear systems", "matrix factorizations", "least squares", eigenvalues, and numerical methods. Concepts are introduced with clear motivation, examples, and algorithms that can be implemented on a computer. This approach helps students understand not only the mathematics, but also how and why these tools are used in real systems like sensing, estimation, and control.
Overall, the book is ideal for beginners who want to apply linear algebra immediately in robotics, machine learning, and engineering. Its strong focus on "applications", "computation", and "problem-solving" makes it an accessible and effective learning resource. Rather than proving every theorem, it prepares students to confidently use linear algebra as a working tool in modern technical fields.
Book Details & Specifications
Title:
Notes for Computational Linear Algebra by Jessy Grizzle
Publisher:
University of Michigan
Year:
2020
Pages:
282
Type:
PDF
Language:
English
ISBN-10 #:
B08PW3YH4P
ISBN-13 #:
978-1482258714
License:
External Educational Resource
Amazon:
Amazon
About the Author: Jessy W. Grizzle
The author Jessy W. Grizzle
is a leading robotics engineer and professor at the University of Michigan, known for his work in "robotics", "control systems", and engineering education. He focuses on making complex mathematics understandable and useful for real-world applications. As the author of "Notes for Computational Linear Algebra", Grizzle emphasizes "computational learning", "practical applications", and "problem-solving". His teaching approach helps students apply linear algebra directly to robotics, machine learning, and engineering systems with confidence and clarity.
Read or Downloadable Notes for Computational Linear Algebra
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