Cambridge, MA – According to GitHub, Julia ranks #4 on the list of the top machine learning projects by contribution and #6 on the list of top machine learning languages on GitHub.
Furthermore, 11.5% of developers want to learn Julia in 2019 (HackerRank 2019 Developer Skills Report).
Julia co-creator and Julia Computing CEO Viral Shah says: “Artificial intelligence and machine learning practitioners worldwide are choosing Julia for its superior speed, performance, syntax and ease of use – especially for parallel and distributed computing including GPUs and TPUs. There are hundreds of exciting new machine learning and artificial intelligence projects in Julia including cataloguing every visible object in the universe and identifying life-saving medicines and bringing them to market, and we can’t wait to see what other new Julia projects are in development in 2019 and beyond!”
About Julia and Julia Computing
Julia is the fastest high performance open source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and other scientific and numeric computing applications. Julia solves the two language problem by combining the ease of use of Python and R with the speed of C++. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. Julia has been downloaded more than 3.2 million times and is used at more than 1,500 universities. Julia co-creators are the winners of the 2019 James H. Wilkinson Prize for Numerical Software. Julia has run at petascale on 650,000 cores with 1.3 million threads to analyze over 56 terabytes of data using Cori, one of the ten largest and most powerful supercomputers in the world.
Julia Computing was founded in 2015 by all the creators of Julia to develop products and provide professional services to businesses and researchers using Julia.
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