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By Aran Davies
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8 years of experience
Aran Davies is a full-stack software development engineer and tech writer with experience in Web and Mobile technologies. He is a tech nomad and has seen it all.
Julia programming language has emerged as a popular choice in data science, machine learning, and scientific computational projects. Language has distinct characteristics and advantages, and it has many uses.
A brief introduction to Julia Programming Language
Julia is a high-level and general-purpose programming language. This free and open-source language is dynamically typed. Julia is a compiled language, however, it’s compiled at the run-time.
Jeff Bezanson, Stefan Karpinski, Viral B. Shah, and Alan Edelman started developing Julia in 2009. They launched this language in 2012.
The creators of Julia wanted to create a high-level language that’s fast. You can use this general-purpose language for projects like web development, however, it’s excellent for statistics and machine learning.
Advantages of Julia Programming Language
Julia offers the following advantages:
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- It’s free and open-source.
- Julia is easy to learn.
- The syntax of Julia makes it highly suitable for mathematical operations, statistical programming, machine learning, and data science.
- Julia is fast. It’s a compiled language, which contributes to its performance. Its creators designed it for performance.
- The integrated package manager of Julia is very easy to use.
- Julia a dynamically-typed language, which offers flexibility.
- It’s an extensible language.
- Julia has a growing and vibrant developers’ community. It contributes greatly to the development of this language.
- Julia makes it easy for you to implement functional behaviors. You can do that for many arguments and programming patterns. The “multiple dispatch” model followed by Julia makes this possible.
- Julia offers macros and meta-programming capabilities.
- Interoperability with languages like C and Python is another advantage of Julia.
- With Julia, you can automatically generate codes for several argument types.
- Julia automated memory management with features like co-routines and lightweight green threading.
- This language supports Unicode and UTF-8 encoding.
- Julia is a versatile language.
How popular is Julia?
The popularity of Julia is growing. The TIOBE Index ranks it as the 25th most popular language. The Stack Overflow Developer Survey report mentions Julia as the 33rd most popular language. This report indicates it as the 5th most-loved language.
Where can you use Julia?
You can use Julia in projects involving complex mathematical computations. Julia is a great choice for scientific computing. You can use it in artificial intelligence and machine learning projects. Many data science projects use Julia since it’s good for data visualization. You can use Julia for web development and game development too.
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Google, AstraZeneca, BlackRock, Intel, Microsoft, Moderna, Pfizer, NASA, Federal Reserve Bank of New York, Federal Aviation Administration, NVIDIA, Cisco, Cancer Research UK, QuantEcon, and the Climate Modeling Alliance are some of the prominent organizations that use Julia.
Julia is increasingly used in data science, machine learning, and scientific computing projects. Python is a dominant language in all of these spaces. While Julia has many promises, it won’t replace Python. Python is a powerful programming language too. Both languages will be in use.
A growing number of developers are expressing interest in Julia. However, hiring Julia developers can take time depending on your local labor market. The number of Julia developers can be low in several regions. Have a backup plan to hire Python developers if you can’t find Julia programmers.
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