Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects simply to a non-technical, business audience. Over…
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++.
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:
Julia is made available under the MIT license and the source code is available on GitHub.
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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Margaret is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical business audience. Over the past twenty years, her IT definitions have been published by Que in an encyclopedia of technology terms and cited in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine, and Discovery Magazine. She joined Techopedia in 2011. Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages.
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