Based on our record, GitHub seems to be a lot more popular than Apertium. While we know about 2048 links to GitHub, we've tracked only 3 mentions of Apertium. 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.
For GitHub, we set up information about the author of commits, like this:. - Source: dev.to / 1 day ago
A GitHub account. If you don't have one, you can sign up at GitHub. - Source: dev.to / 2 days ago
Practice, practice, and more practice are necessary for mastering the skill of coding. To make sure you understand the concepts you've learned, start with easy exercises and small projects. Practice problems can be found on sites like GitHub or Reddit, or on platforms like HackerRank and LeetCode. - Source: dev.to / 3 days ago
To realize continuous integration in practice, we rely on version control systems(VCS) such as Git, code repositories such as GitHub, and build automation tools such as GitHub Actions. - Source: dev.to / 3 days ago
Often, when we set up version control initial files for a project, we tend to log onto the Github website to create our repositories, clone, and push our projects. While this method works, it can be argued that it is not as efficient. We can manage our GitHub repositories, from creating the repo to maintaining the different versions, right from our terminal. In this article, we will go through the process of... - Source: dev.to / 8 days ago
This is very cool, looking forward to it! I've been doing the same thing with Spanish Wikipedia articles for a while, using a few lines of Bash + Regex. I was using Apertium for it. https://apertium.org/ It's definitely worse than most ML-based solutions, but it works reliably and fast; you can run it entirely offline. With Spanish translations, the main problem I was facing is lack of vocabulary, so I created - Source: Hacker News / 9 months ago
I used to keep track of the state of machine translation some years back. I think the way you measure the success of an automated translation is edit distance, i.e. How many manual edits you need to make to a translated text before you reach some acceptable state. I suppose it's somewhat subjective, but it is possible to construct a benchmark and allow for multiple correct results. The best resources I knew back... - Source: Hacker News / almost 2 years ago
Apertium is one of them. We make open-source rule-based machine translation systems, and our core tools are in C++. A few of our proposed ideas involve modifying those C++ tools with new features or improvements to existing features. Source: about 3 years ago
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Google Translate - Google's free service instantly translates words, phrases, and web pages between English and over 100 other languages.
BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Microsoft Translator - Microsoft Translator is your door to a wider world.
Visual Studio Code - Build and debug modern web and cloud applications, by Microsoft
DeepL Translator - DeepL Translator is a machine translator that currently supports 42 language combinations.