Linear Algebra Tutor

Online linear algebra tutoring at My Engineering Buddy

You have reached the best place to learn linear algebra. We have a team of expert online linear algebra tutors to help you understand the theory and applications of the subject. Our experienced virtual private tutorials will help you at a pace that will maximize your understanding of the subject.

The MEB tutors can also help you with offline homework and assignments, exam preparations, grasping problem-solving methods, preparing cheat sheets, and applying linear algebra in other disciplines. These 1-on-1 sessions are beneficial for students who learn much more efficiently in an interactive and focused environment compared to a regular classroom set-up.

What is linear algebra?

Linear algebra is a discipline of mathematics dealing with vectors and their spaces, matrices and, linear transformations. It is the systematic theory to solve systems of linear equations with finite unknown variables. An important concept is ‘span,’ the space covering linear combinations of a set of given vectors.

Applications of linear algebra

Linear algebra is a relatively young stream of math that has broad applications, from modern algebra and mathematical physics to machine learning and data science. Academically, we extensively use it in many areas of mathematics, including probability theory, differential equations, and multivariate calculus and fields like economics, physics, chemistry, engineering, and psychology. Linear Algebra is in action whenever we perform an Internet search or use Global Positioning System (GPS).

How is linear algebra used in machine learning?

Linear algebra is the most critical maths skill for machine learning. It is directly and indirectly used in machine learning. For example, SVD and Eigenvectors are requisite topics for machine learning students and professionals. Linear algebra is also involved in other areas of math that are, in turn, helps in machine learning. Matrices effectively represent many machine learning models and datasets.

What is linear algebra in data science?

Linear algebra is foundational for both beginners and seasoned practitioners of data science. Data preprocessing and transformation and model evaluation are dependent on linear algebra. Vectors and matrices are mathematically suited to represent large volumes of information.

Where do I get free tutoring on linear algebra?

Free 1:1 tutoring is not possible anywhere but if you want to learn by watching some prerecorded videos then you can use Khan Academy.

Textbooks for linear algebra reference

• Introduction to Linear Algebra by Gilbert Strang. Publisher: Wellesley-Cambridge Press
• Introduction to Applied Linear Algebra: Vectors, Matrices, and Least Squares by Stephen Boyd. Publisher: Cambridge University Press
• Linear Algebra by Stephen Friedberg, Arnold Insel, Lawrence Spence. Publisher: Pearson
• Linear Algebra Done Right (Undergraduate Texts in Mathematics) by Sheldon Axler. Publisher: Springer
• Linear Algebra and Learning from Data by Gilbert Strang. Publisher: Wellesley-Cambridge Press
• Differential Equations and Linear Algebra by Gilbert Strang. Publisher: Wellesley-Cambridge
• Linear Algebra and Optimization for Machine Learning: A Textbook by Charu C. Aggarwal. Publisher: Springer