TLDR
Julia promises performance comparable to statically typed compiled languages (like C) while keeping the rapid development features of interpreted languages. This performance is achieved by just-in-time (JIT) compilation. In interpreted languages we pay an overhead for each time we execute an instruction. We want to use vectorized operations or specialized implementations that take data structures (e.g. arrays, dataframes) as input and handle them in a single call. In this post, we will try to show how the mindset and limitations when programming in interpreted languages can be achieved out of the box.via the TL;DR App
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Written by dmoura | Computer Scientist and Engineer passionate about Data and Algorithms
