Julia Programming Language

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What Does Julia Programming Language Mean?

Julia is an open source high-level, high-performance dynamic programming language designed at MIT for large-scale, partial-differential equation simulations and distributed linear algebra.


Julia’s ability to support scientific computing makes it a good choice for designing machine learning models and AI simulations.

The Julia programming language has a sophisticated compiler and supports distributed parallel execution. It is known for its numerical accuracy and mathematical function library, as well as its robust ecosystem of tools for optimization, statistics, parallel programming and data visualization.

Julia is expected to play an important role in the future of data science and artificial intelligence because it combines Python’s user-friendly scripting features with the high performance of compiled languages like C++.

Techopedia Explains Julia Programming Language

Julia is one of the few open-source platforms for training machine learning models. (Until recently, machine learning models have been trained or developed primarily in R and Python.)

While Julia is considered to be a general-purpose language, data scientists are using many of its features for numerical analysis and computational science.

Compared to other platforms, Julia is known for being easy to use. It is also known for being:

  • As fast as C.
  • As dynamic as Ruby.
  • As general as Python.
  • As statistics-friendly as R.
  • As powerful as Matlab for linear algebra.
  • As natural as Perl for string processing.

Julia is made available under the MIT license and the source code is available on GitHub.

Julia vs. Python for Machine Learning Jobs

Although Julia is faster than Python or C, at this time its community and library collection is much smaller. For this reason alone, most experts recommend that IT professionals working with machine learning applications learn Python first.

At this time there are fewer job postings calling for developers who know Julia, but that is expected to change as the language matures and its applications broaden beyond data science.


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