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Name License Source model Target uses Status Platforms Apache Mynewt: Apache 2.0: open source: embedded: active: ARM Cortex-M, MIPS32, Microchip PIC32, RISC-V: BeRTOS: Modified GNU GPL: open source
Automatic customization and visualization of phylogenetic trees iTOL - interactive Tree Of Life [6] annotate trees with various types of data and export to various graphical formats; scriptable through a batch interface Microreact [7] Link, visualise and explore sequence and meta-data using phylogenetic trees, maps and timelines OneZoom [8]
A desktop environment is a collection of software designed to give functionality and a certain look and feel to an operating system.. This article applies to operating systems which are capable of running the X Window System, mostly Unix and Unix-like operating systems such as Linux, Minix, illumos, Solaris, AIX, FreeBSD and Mac OS X. [1]
The Linux Desktop Testing Project (LDTP) is a testing tool that uses computer assistive technology [7] to automate graphical user interface (GUI) testing. [8] The GUI functionality of an application can be tested in Linux , macOS , Windows , Solaris , FreeBSD , and embedded system environments. [ 9 ]
A latent space, also known as a latent feature space or embedding space, is an embedding of a set of items within a manifold in which items resembling each other are positioned closer to one another. Position within the latent space can be viewed as being defined by a set of latent variables that emerge from the resemblances from the objects.
Other latent variables correspond to abstract concepts, like categories, behavioral or mental states, or data structures. The terms hypothetical variables or hypothetical constructs may be used in these situations. The use of latent variables can serve to reduce the dimensionality of data. Many observable variables can be aggregated in a model ...
Linux, macOS: Python: Python: No No Yes No Yes Yes Yes Yes No Yes No [7] Deeplearning4j: Skymind engineering team; Deeplearning4j community; originally Adam Gibson 2014 Apache 2.0: Yes Linux, macOS, Windows, Android (Cross-platform) C++, Java: Java, Scala, Clojure, Python , Kotlin: Yes No [8] Yes [9] [10] No Computational Graph Yes [11] Yes Yes ...
Anaconda is a distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. Anaconda distribution includes data-science packages suitable for Windows, Linux, and macOS ...