줄리아

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Pythagoras0 (토론 | 기여)님의 2021년 2월 17일 (수) 01:44 판
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  • The paper reviews what the Julia programming language is and its staying power relative to other popular programming languages.[1]
  • , it’s super easy to use python and R packages within Julia.[2]
  • Julia is a MIT certified free open source, high level , high performance programming language.[2]
  • Julia uses the JIT(Just in Time) – compiler which generates native machine code.[2]
  • What if I tell you Julia passes all these criterias.[2]
  • Kamiński: Here it is crucial to define what I understand by Julia being ready for production.[3]
  • Well, you can easily "ship" a Julia project and expect that anyone on any environment should be able to relatively effortlessly run it.[3]
  • I do not see Julia as a language that is best suited for any kind of project.[3]
  • Each programming language has its niche, and the niche of Julia is high performance computing/data science (or however you call it).[3]
  • Julia is a high-performance, high-level, and dynamic programming language that leans toward technical, numerical, and statistical computing.[4]
  • Asked to explain why the name Julia, Stefan Karpinski said in an interview, “That's everybody's favorite question.[4]
  • Julia is now backed by more than 700 active contributors.[4]
  • Where Julia shines is in its ability to balance speed and performance.[4]
  • Julia entered the market when data is making organisations more futuristic, agile, and effective.[5]
  • He furthers it by saying that unlike other compiled languages like C that are compiled before execution, Julia is compiled at run-time.[5]
  • Users with a preference for the grammar of graphics style API might like the pure Julia Gadfly.jl plotting package.[5]
  • VegaLite.jl provides the Vega-Lite grammar of interactive graphics interface as a Julia package.[5]
  • Now Julia is waiting for us to input our code, evaluating it line by line.[6]
  • You can confirm that by checking the Terminal prompt, which says julia> .[6]
  • So we can use Julia like a simple calculator.[6]
  • This also tells us that Julia does not allow using variables without properly initializing them.[6]
  • My entire research is in Julia nowadays, and I don't regret it.[7]
  • Julia's package library is small and still coming of age – but for you, that's a great thing![8]
  • In contrast Julia looks like Python or Matlab with a twist.[9]
  • Economists at the Federal Reserve Bank of New York have adopted Julia for modeling.[9]
  • Because it is so new, Julia’s code base can be lacking.[9]
  • Many Julia libraries are still updating and expanding, and new features are added to the language every few months.[9]
  • Recently, Julialang also celebrated the addition of composable multi-threaded parallelism, taking a page out of the Golang’s book.[10]
  • Julialang is a high-performance, dynamically-typed, open source language that shines in scientific computing.[10]
  • In January 2019, Julia Computing won the Wilkinson Prize for Numerical Software, which awards outstanding contributions in the field.[10]
  • According to the 2019 survey, 73% of users and developers use Julia for research.[10]
  • Where does Julia stand in Machine Learning?[11]
  • According to the paper, Julia is rapidly becoming a highly competitive language in data science and general scientific computing.[11]
  • Julia is seeing major uptake in the scientific community.[12]
  • The next-generation climate model is being built in Julia.[12]
  • Julia is among the few languages being used on the biggest supercomputers.[12]
  • Everybody would enjoy using Julia for their work.[12]
  • Keno Fischer, Julia Computing co-founder and CTO (Tools) discussed Julia and Julia Computing in a recent interview.[13]
  • Julia is a modern open-source language for data science, machine learning and scientific computing that has gained increasing attention.[13]
  • Julia uses type inference and just-in-time compilation to compile high-level user code to machine code on the fly.[14]
  • Python has been around for a long time than Julia and soon it has become the preferred choice for developers and programmers.[15]
  • Julia has been emerging as a potential competitor for Python with predominant features and Python is no lagging behind.[15]
  • Julia, an excellent choice for numerical computing and it takes lesser time for big and complex codes.[15]
  • Julia undoubtedly beats Python in the performance and speed category.[15]
  • With Julia, it was harder to find off-the-shelf libraries.[16]
  • Julia is the newcomer and it shows, incorporating state-of-the-art language design features.[16]
  • Julia's handling of data is lacking in terms of file types and options supported at present.[16]
  • That said, Python, Julia and R can all call functions from each other.[16]
  • If you have no clue about Julia, yet you want to master this language, this is an apt starter for you.[17]
  • This tutorial will allow you to learn Julia by doing it simultaneously.[17]
  • This conference comprises of talks and workshops which intends to cover a wide range of applications and tutorials of Julia Programming.[17]
  • Here’s the Youtube videos from Julia Conference 2014.[17]
  • Consider recent stats on Julia adoption.[18]
  • By January 1, 2019, reports Julialang.org, the total downloads of Julia reached 7.3 million.[18]
  • In his SC19 talk, Edelman noted that as of October 2019 there were 3,119 Julia packages available, up from 1,688 at the year’s start.[18]
  • Whether Julia will challenge Python the way Python once challenged and then surpassed Java is an interesting question being bandied about.[18]
  • Now Julia v1.0 and JuMP v0.19 have been released.[19]
  • There were major upgrades in both Julia and JuMP including many breaking changes.[19]
  • I based my assessment on Julia’s unique combination of convenient syntax with uncompromising performance.[20]
  • JuliaCon, the annual Julia convention, took place (online, of course).[20]
  • At its best, Julia can approach or match the speed of C. Julia is interactive.[21]
  • Julia includes a REPL (read-eval-print loop), or interactive command line, similar to what Python offers.[21]
  • Julia combines the benefits of dynamic typing and static typing.[21]
  • Julia can call Python, C, and Fortran libraries.[21]
  • Julia is now listed among the world’s 50 most-popular programming languages, according to one index.[22]
  • Julia circumvents that two-language problem because it runs like C, but reads like Python.[22]
  • “I fell in love with the speed of Julia,” he says.[22]
  • To all appearances, using Julia is like coding in Python: type a line, get a result.[22]
  • Julia, a zippy programming language that has roots at MIT, has published the results of its 2020 annual user survey.[23]
  • But Julia, which developer analyst firm RedMonk has rated as a language to watch, does have decent support behind it too.[23]
  • "The more experience people gain with Julia, the less they want to use anything else.[23]
  • The most frequently used languages after Julia are Python, and then Bash/Shell/PowerShell.[23]
  • In an interview with InfoWorld in April 2012, Karpinski said of the name "Julia": "There's no good reason, really.[24]
  • Julia 1.1 was released in January 2019 with, e.g., a new "exception stack" language feature.[24]
  • Julia 1.1.x releases are no longer maintained).[24]
  • Packages that work in Julia 1.0.x should work in 1.1.x or newer, enabled by the forward compatible syntax guarantee.[24]

소스

  1. ↑ An Overview of the Julia Programming Language
  2. ↑ 2.0 2.1 2.2 2.3 Julia – Programming Language
  3. ↑ 3.0 3.1 3.2 3.3 Is Julia Production Ready? Q&A with Bogumił Kamiński
  4. ↑ 4.0 4.1 4.2 4.3 Things to Know About Julia Programming Language
  5. ↑ 5.0 5.1 5.2 5.3 Julia: Programming Language for the Future
  6. ↑ 6.0 6.1 6.2 6.3 Julia Programming Projects
  7. ↑ What were the reasons for selecting Julia as programming language?
  8. ↑ Google Summer of Code Archive
  9. ↑ 9.0 9.1 9.2 9.3 A Quick Tour of the Julia Language
  10. ↑ 10.0 10.1 10.2 10.3 Julia: The programming language of the future?
  11. ↑ 11.0 11.1 Julia Language in Machine Learning: Algorithms, Applications, and Open Issues
  12. ↑ 12.0 12.1 12.2 12.3 Why I Wrote a Julia Programming Book
  13. ↑ 13.0 13.1 Julia: The Programming Language Of The Future
  14. ↑ The Julia programming language: the future of scientific computing
  15. ↑ 15.0 15.1 15.2 15.3 Julia Vs Python: Will it unseat the king of programming?
  16. ↑ 16.0 16.1 16.2 16.3 Which numerical computing language is best: Julia, MATLAB, Python or R?
  17. ↑ 17.0 17.1 17.2 17.3 Best Resources to Learn Julia Programming
  18. ↑ 18.0 18.1 18.2 18.3 Julia Programming’s Dramatic Rise in HPC and Elsewhere
  19. ↑ 19.0 19.1 Julia – Changhyun Kwon
  20. ↑ 20.0 20.1 The unreasonable effectiveness of the Julia programming language
  21. ↑ 21.0 21.1 21.2 21.3 Julia vs. Python: Which is best for data science?
  22. ↑ 22.0 22.1 22.2 22.3 Julia: come for the syntax, stay for the speed
  23. ↑ 23.0 23.1 23.2 23.3 Programming languages: Julia users most likely to defect to Python for data science
  24. ↑ 24.0 24.1 24.2 24.3 Julia (programming language)

메타데이터

위키데이터

Spacy 패턴 목록

  • [{'LEMMA': 'Julia'}]
  • [{'LEMMA': 'JuliaLang'}]
  • [{'LOWER': 'the'}, {'LOWER': 'julia'}, {'LEMMA': 'Language'}]
  • [{'LOWER': 'julia'}, {'LOWER': 'programming'}, {'LEMMA': 'language'}]
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