Julia is a high-level, dynamic programming language, designed to give users the speed of C/C++ while remaining as easy to use as Python. This means that developers can solve problems faster and more effectively. Julia is great for computationally complex problems. Julia is a general-purpose language also and can be used for tasks like Web Development, Game Development, and more. Many view Julia as the next-generation language for Machine Learning and Data Science . It was developed mainly for numerical computation purpose, and it helps eliminate performance issues. It will provide an environment which is good enough to develop applications that require high performances. Julia is JIT Compiled. Write code that looks interpreted, and yet it gets to run as just as fast as compiled code. No need to vectorize code for performance, de vectorized code is fast. •Optionally Typed. Do some rapid prototyping with maximum flexibility, and then optimize for performance. Nice Mathematical Syntax. Builds upon and goes much further than classical mathematical languages like Fortran, Mat lab, and Mathematica. •General purpose. Get code from the package manager to perform all sort of tasks, from reading multiple types of databases, to data visualization, or running an HTTP server. •Similar to Ruby in Dynamic types.
