A series on automatic differentiation in Julia.

Part of the appeal in Julia is that it’s designed to be a high-performance language for scientific computing. Like other scientific languages (e.g., R, Matlab, etc) it has 1-based indexing rather than 0-based indexing (Python, C , etc). Julia code is automatically compiled giving you performance that is comparable to compiled languages like C , without the hassle of actually having to deal with the compiler yourself. But we’ve all heard the sales pitch for Julia before, there’s no need for me to repeat it here, and anyway I kinda just want to dive into the code.