Julia – A Fresh Approach to Numerical Computing

This post is authored by Viral B. Shah, co-creator of the Julia language and co-founder and CEO at Julia Computing, and Avik Sengupta, head of engineering at Julia Computing. The Julia language provides a fresh new approach to numerical computing, where there is no longer a compromise between performance and productivity. A high-level language that makes writing natural mathematical code easy, with runtime speeds approaching raw C, Julia has been used to model economic systems at the Federal Reserve, drive autonomous cars at University of California Berkeley, optimize the power grid, calculate solvency requirements for large insurance firms, model the US mortgage markets and map all the stars in the sky. It would be no surprise then that Julia is a natural fit in many areas of machine learning. And the powers of Julia make it a perfect language to implement these algorithms.