Julia
MATLAB
Python
GNU Octave
Rust
Wolfram Mathematica
Clojure
Scilab
Codeconfig.dev
We recommend LibHunt Julia for discovery and comparisons of trending Julia projects.
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Codeconfig.dev{"data_science" => "Data scientists who require a fast and flexible language for data manipulation and analysis.", "machine_learning" => "Developers looking to implement machine learning models that benefit from Julia's performance.", "numerical_analysis" => "Engineers and analysts conducting numerical analysis that demands high computational efficiency.", "scientific_computing" => "Researchers and scientists working on mathematical, statistical, and computational problems."}
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Based on our record, Julia seems to be more popular. It has been mentiond 130 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
If you're looking for a language that aims to solve the "two-language problem" like Mojo, but want something more open, more mature and less influenced by VC funding, check out Julia: https://julialang.org/. - Source: Hacker News / 4 months ago
The problem with MATLAB is that idiomatic MATLAB style (every operation returns a fresh matrix) can easily become very inefficient: it leads to countless heap memory allocations of new matrices, resulting in low data-access locality, i.e. Your data is needlessly copied around in slow DRAM all the time, rather than being kept in the fastest CPU cache. Julia's MATLAB-inspired syntax is at least as nice, but the... - Source: Hacker News / 9 months ago
In this post, We will learn how to simulate MRI physics In the Julia programming language, a free and open source programming language That excels especially in scientific computing. - Source: dev.to / 11 months ago
Mine is Julia, although I don't use diary. Nowadays I like SuperCollider. https://julialang.org. - Source: Hacker News / about 1 year ago
> I was active in the Python community in the 200x timeframe, and I daresay the common consensus is that language didn't matter and a sufficiently smart compiler/JIT/whatever would eventually make dynamic scripting languages as fast as C, so there was no reason to learn static languages rather than just waiting for this to happen. To be very pedantic, the problem is not that these are dynamic languages _per se_,... - Source: Hacker News / about 1 year ago
MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming
Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
GNU Octave - GNU Octave is a programming language for scientific computing.
Rust - A safe, concurrent, practical language
Wolfram Mathematica - Mathematica has characterized the cutting edge in specialized processing—and gave the chief calculation environment to a large number of pioneers, instructors, understudies, and others around the globe.
Clojure - Clojure is a dynamic, general-purpose programming language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming.