Macchina is an open source software toolkit for quickly building embedded applications for the Internet of Things that run on Linux-based IoT gateways and devices like the Raspberry Pi, Beaglebone, RED Brick or Galileo/Edison.
Runs on Embedded Linux devices with as little as 32 MB of RAM, as well as desktop Linux and OS X. Develop and test on desktop machine, then easily deploy to embedded device.
It runs on Linux-based devices, including IoT gateways, industrial computing devices, and prototyping platforms like the Raspberry Pi, Beaglebone and MangOH.
Expo CLI is a command line interface for developing Expo apps. It also includes a web-based interface (Expo Dev Tools) for using some of the most often used features also from a quick to use graphical interface.
Expo apps are React Native apps which contain the Expo SDK. The SDK is a native-and-JS library which provides access to the device's system functionality (things like the camera, contacts, local storage, and other hardware). That means you don't need to use Xcode or Android Studio or write any native code, and it also makes your pure-JS project very portable because it can run in any native environment containing the Expo SDK.
Expo also provides UI components to handle a variety of use-cases that almost all apps will cover but are not baked into React Native core, e.g. icons, blur views, and more.
Finally, the Expo SDK provides access to services which typically are a pain to manage but are required by almost every app. Most popular among these: Expo can manage your Assets for you, it can take care of Push Notifications for you, and it can build native binaries which are ready to deploy to the app store.
Vue Native is a wrapper around React Native APIs, which allows you to use Vue.js and compose rich mobile User Interface.
Vue is a progressive framework for building user interfaces. Unlike other monolithic frameworks, Vue is designed from the ground up to be incrementally adoptable. The core library is focused on the view layer only and is easy to pick up and integrate with other libraries or existing projects.
Mezzanine is a powerful, consistent, and flexible content management platform. Built using the Django framework, Mezzanine provides a simple yet highly extensible architecture that encourages diving in and hacking on the code. Mezzanine is BSD licensed and supported by a diverse and active community.
In some ways, Mezzanine resembles tools such as Wordpress, providing an intuitive interface for managing pages, blog posts, form data, store products, and other types of content. But Mezzanine is also different. Unlike many other platforms that make extensive use of modules or reusable applications, Mezzanine provides most of its functionality by default. This approach yields a more integrated and efficient platform.
Hierarchical page navigation
Save as draft and preview on site
Drag-and-drop page ordering
In-line page editing
Drag-and-drop HTML5 forms builder with CSV export
SEO friendly URLs and metadata
E-commerce / Shopping cart module (Cartridge)
Configurable dashboard widgets
Free Themes, and a Premium Themes Marketplace
User accounts and profiles with email verification
Translated to over 35 languages
Sharing via Facebook or Twitter
Custom templates per page or blog post
Twitter Bootstrap integration
API for custom content types
Search engine and API
Mezzanine is an open source project managed using both the Git and Mercurial version control systems.
1) Developer Ready
2) Instant Feedback
Fast interactive watch mode runs only test files related to changed files and is optimized to give signal quickly.
3) Snapshot Testing
Capture snapshots of React trees or other serializable values to simplify testing and to analyze how state changes over time.
What is Redmine? Redmine is a flexible project management web application. Written using the Ruby on Rails framework, it is cross-platform and cross-database.
Redmine is open source and released under the terms of the GNU General Public License v2 (GPL).
It is a cross-platform, cross-database, and open source tool that also has issue-tracking features. Users can manage multiple projects and subprojects, and have access to many planning, tracking, and documenting features available from similar commercial products.
Redmine has a news area where members can publish news items. It allows the creation of documents, such as user documentation or technical documentation, which can be downloaded by others. A Files module is a table that lists all uploaded files and its details.
Users can easily create project wikis with the help of a toolbar. Other features include custom fields for creating additional information, and a Repository to view a given revision and the latest commits. The software can be configured to receive emails for issue creation and comments. It also supports particular versions of different databases, such as MySQL, PostgreSQL, MS SQL Server, and SQLite. API and plug-ins are also available.
Multiple projects support
Flexible role based access control
Flexible issue tracking system
Gantt chart and calendar
News, documents & files management
Feeds & email notifications
Per project wiki
Per project forums
Custom fields for issues, time-entries, projects and users
SCM integration (SVN, CVS, Git, Mercurial and Bazaar)
What is H2O in Machine Learning? H2O.ai is a leader in the 2018 Gartner Magic Quadrant for Data Science and Machine Learning Platforms.
H2O is open-source software for big-data analysis. It is produced by the company H2O.ai. H2O allows users to fit thousands of potential models as part of discovering patterns in data.
The H2O software runs can be called from the statistical package R, Python, and other environments. It is used for exploring and analyzing datasets held in cloud computing systems and in the Apache Hadoop Distributed File System as well as in the conventional operating-systems Linux, macOS, and Microsoft Windows.
The H2O software is written in Java, Python, and R. Its graphical-user-interface is compatible with four browsers: Chrome, Safari, Firefox, and Internet Explorer.
H2O is a Java-based software for data modeling and general computing. The H2O software is many things, but the primary purpose of H2O is as a distributed (many machines), parallel (many CPUs), in memory (several hundred GBs Xmx) processing engines.
There are two levels of parallelism:
- within node - across (or between) nodes The goal of H2O is to allow simple horizontal scaling to a given problem in order to produce a solution faster. The conceptual paradigm MapReduce, along with a good concurrent application structure, enable this type of scaling in H2O.
Video for H2O https://www.youtube.com/watch?v=9W_c2Ec23PM