18.06SC Linear Algebra (Fall 2011, MIT OCW): Lecture 16

18.06SC Linear Algebra

18.06SC Linear Algebra (Fall 2011, MIT OCW). Taught by Prof. Gilbert Strang, this course covers matrix theory and linear algebra, emphasizing topics useful in other disciplines such as physics, economics and social sciences, natural sciences, and engineering. This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include: a complete set of lecture videos, summary notes, problem solving videos, and a full set of exams and solutions. (from ocw.mit.edu)

Lecture 16 - Projections onto Subspaces

We often want to find the line (or plane, or hyperplane) that best fits our data. This amounts to finding the best possible approximation to some unsolvable system of linear equations Ax = b. The algebra of finding these best fit solutions begins with the projection of a vector onto a subspace.

References

Projections onto Subspaces
We often want to find the line (or plane, or hyperplane) that best fits our data. Lecture Video and Summary. Suggested Reading. Problem Solving Video.

Go to the Course Home or watch other lectures:

I. Ax=b and the Four Subspaces

Lecture 01 - The Geometry of Linear Equations

Lecture 02 - An Overview of Key Ideas

Lecture 03 - Elimination with Matrices

Lecture 04 - Multiplication and Inverse Matrices

Lecture 05 - Factorization into A = LU

Lecture 06 - Transposes, Permutations, Vector Spaces

Lecture 07 - Column Space and Nullspace

Lecture 08 - Solving Ax = 0: Pivot Variables, Special Solutions

Lecture 09 - Solving Ax = b: Row Reduced form R

Lecture 10 - Independence, Basis and Dimension