
Julia
MATLAB
Python
GNU Octave
Rust
Wolfram Mathematica
Clojure
Scilab
Adobe Analytics
Google Analytics
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Julia
Adobe Analytics{"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."}
Based on our record, Julia seems to be a lot more popular than Adobe Analytics. While we know about 130 links to Julia, we've tracked only 2 mentions of Adobe Analytics. 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 / 10 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
Google Analytics was launched in 2005 as a tool for reporting web traffic. It is one of many web analytics tools. Adobe Analytics and Hubspot Analytics are example competitors to Google Analytics. - Source: dev.to / over 4 years ago
What it is: Adobe Analytics provides a set of tools that lets you collect, measure, and explore data you can use to predict traffic and gain insights. It has an interactive analytics workspace that helps you easily drag and drop data tables, visualizations, and components. - Source: dev.to / almost 5 years ago
MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming
Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.
Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.
Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.
GNU Octave - GNU Octave is a programming language for scientific computing.
Heap - Analytics for web and iOS. Heap automatically captures every user action in your app and lets you measure it all. Clicks, taps, swipes, form submissions, page views, and more.