Best Linear Algebra
Gilbert Strang’s Linear Algebra course through MIT OpenCourseWare provides a foundational understanding of this essential mathematical discipline. The lectures, developed over decades by renowned professor Gilbert Strang, are known for their clarity and accessibility. This series is ideal for studen...
The 3Blue1Brown Essence of Linear Algebra series presents a visual introduction to fundamental linear algebra concepts. Grant Sanderson’s animated explanations leverage geometric intuition to clarify matrix operations, vector spaces, and transformations. This resource is beneficial for students, res...
Jack Dongarra is an American computer scientist and professor at the University of Tennessee specializing in high-performance computing (HPC). He has led or contributed to the creation of essential numerical software libraries, including LINPACK, BLAS, LAPACK, and the Message Passing Interface (MPI)...
Gene Golub was an American computer scientist and mathematician widely considered a founding figure in numerical linear algebra. As a professor at Stanford University, he co-authored the standard textbook "Matrix Computations" and developed foundational algorithms for computing the singular value de...
Cleve Moler is an American mathematician and computer scientist who created MATLAB in the late 1970s at the University of New Mexico as an interactive interface to the LINPACK and EISPACK linear algebra libraries. In 1984 he co-founded MathWorks with Jack Little to commercialize MATLAB, which became...
James Demmel is a professor of computer science and mathematics at the University of California, Berkeley. He is best known for his contributions to numerical linear algebra and high-performance computing, serving as chief architect of LAPACK and ScaLAPACK, widely used dense linear algebra software...
Ravi Kannan is an Indian computer scientist known for his contributions to theoretical computer science and applied mathematics. He is affiliated with Microsoft Research India and has held academic positions including at Carnegie Mellon University and Yale University. His work includes foundational...
Using frameworks like Qiskit to simulate quantum circuits (e.g., Shor's or Grover's algorithms) requires understanding quantum mechanics principles, linear algebra (tensor products), and quantum gates. While the tools are improving, simulating complex, error-corrected circuits remains computationall...
