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Best resources to learnEigenvalues & Eigenvectors

Study sheet

Eigenvalues and eigenvectors are scalar factors and corresponding vectors that remain in the same direction during a linear transformation. You will understand how to calculate them and apply them to systems of differential equations, principal component analysis, and stability analysis.

8 resources · · How we curate

📹Videos(2)

video

Eigenvectors and eigenvalues

Visual explanation from 3Blue1Brown Essence of Linear Algebra

beginner🇬🇧
video

Gilbert Strang: Eigenvalues and Eigenvectors (Differential Equations and Linear Algebra video lectures)

Eight short MIT lectures by Gilbert Strang that apply eigenvalues to differential equations. Topics are diagonalization, matrix powers and Markov matrices, solving linear systems du/dt = Au, the matrix exponential, similar and symmetric matrices, and second-order systems.

intermediate🇬🇧

🎓Courses(4)

course

Essence of Linear Algebra

Grasp determinants with 3Blue1Brown's "Essence of Linear Algebra" course. Visualize and understand this key linear algebra concept.

beginner🇬🇧
course

Linear Algebra (MIT 18.06)

Matrix theory and linear algebra: systems of equations, elimination, vector spaces and subspaces, orthogonality and least squares, determinants, eigenvalues and positive definite matrices. Includes 35 lecture videos plus problem sets and exams with solutions, giving the fluency needed for applied mathematics, engineering and data science.

intermediate🇬🇧
course

Linear Algebra - Foundations to Frontiers

Learn the mathematics behind linear algebra and link it to matrix software development.

intermediate🇬🇧
course

Mathematics for Machine Learning: Linear Algebra

In this course on Linear Algebra we look at what linear algebra is and how it relates to vectors and matrices. Then we look through what vectors and matrices are and how to work with them, including the knotty problem of eigenvalues and eigenvectors, and how to use these to solve problems. Finally we look at how to use these to do fun things with datasets - like how to rotate images of faces and how to extract eigenvectors to look at how the Pagerank algorithm works. Since we're aiming at data-driven applications, we'll be implementing some of these ideas in code, not just on pencil and paper. Towards the end of the course, you'll write code blocks and encounter Jupyter notebooks in Python, but don't worry, these will be quite short, focussed on the concepts, and will guide you through if you’ve not coded before. At the end of this course you will have an intuitive understanding of vectors and matrices that will help you bridge the gap into linear algebra problems, and how to apply these concepts to machine learning.

beginner🇬🇧

🌐Websites(2)

website

Khan Academy Eigenvalues

Interactive lessons and exercises

beginner🇬🇧
website

Wolfram MathWorld

MathWorld is an online mathematics encyclopedia from Wolfram Research offering detailed, browsable articles on topics across the math spectrum, including algebra, geometry, calculus, and number theory. Each entry includes definitions, theorems, formulas, diagrams, worked examples, and links to further reading.

intermediate🇬🇧
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What are the best free resources to learn Eigenvalues & Eigenvectors?

Dantes has curated 8 resources for Eigenvalues & Eigenvectors, including 2 videos, 4 courses, 2 websites. All resources are hand-picked for quality — no algorithmic filler. Browse the full list above to find the format that works best for you.

Is Eigenvalues & Eigenvectors hard to learn?

Eigenvalues & Eigenvectors is approachable at the beginner level — there are resources here specifically for those starting from scratch. As you progress, intermediate and advanced material is also available to take your skills further.

What types of Eigenvalues & Eigenvectors learning resources are available on Dantes?

For Eigenvalues & Eigenvectors, Dantes has curated 2 videos, 4 courses, 2 websites. Each resource type serves a different learning style: videos and YouTube for visual learners, books for depth, courses for structured progression, and websites for quick reference.

How does Dantes select Eigenvalues & Eigenvectors resources?

Dantes is an algorithm-free learning directory. Resources are hand-curated based on quality, accuracy, and usefulness — not engagement metrics or paid placements. The goal is to surface the best learning material for Eigenvalues & Eigenvectors, whether it's a free YouTube series, a classic textbook, or an open courseware from a top university.

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