Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
This conference talk from CppCon 2024 explores the Eigen C++ library for linear algebra applications, presented by Daniel Hanson, former faculty member from the University of Washington's Department of Applied Mathematics/Computational Finance & Risk Management. Discover how Eigen addresses the historical challenges C++ programmers faced when transitioning from Fortran for scientific programming, particularly in fields like quantitative finance, data science, physics, medical research, and game development. Learn about the library's basic setup, advanced features including matrix decompositions for quantitative work, compatibility with STL algorithms, and its integration with the C++26 BLAS interface proposal via std::mdspan in C++23. The presentation highlights Eigen's widespread adoption in prominent projects like TensorFlow, the Stan Math Library, CERN applications, and high-performance quantitative trading strategies, demonstrating its importance in modern scientific programming with C++.
