Julia vs Python vs Stan

Julia

286
393
+ 1
107
Python

109.9K
84.1K
+ 1
6.4K
Stan

41
22
+ 1
0
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      What is Julia?

      Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.

      What is Python?

      Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

      What is Stan?

      A state-of-the-art platform for statistical modeling and high-performance statistical computation. Used for statistical modeling, data analysis, and prediction in the social, biological, and physical sciences, engineering, and business.
      What companies use Julia?
      What companies use Python?
      What companies use Stan?

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      What tools integrate with Julia?
      What tools integrate with Python?
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      Blog Posts

      Sep 29 2020 at 7:36PM
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      WorkOS

      PythonSlackG Suite+17
      6
      1998
      PythonDockerKubernetes+7
      3
      572
      PythonDockerAmazon S3+14
      11
      1861
      Oct 3 2019 at 7:13PM
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      Ably Realtime

      JavaScriptPythonNode.js+8
      4
      3101
      Aug 28 2019 at 3:10AM
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      Segment

      PythonJavaAmazon S3+16
      5
      1845
      JavaScriptPythonPubNub+4
      7
      905
      GitHubPythonReact+42
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      38412
      What are some alternatives to Julia, Python, and Stan?
      R Language
      R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
      MATLAB
      Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.
      Rust
      Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory.
      Go
      Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.
      NumPy
      Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
      See all alternatives
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