In computing, a device driver is a computer program that operates or controls a particular type of device that is attached to a computer or automaton. A driver provides a software interface to hardware devices, enabling operating systems and other computer programs to access hardware functions without needing to know precise details about the hardware being used.
An operating system (OS) is system software that manages computer hardware, software resources, and provides common services for computer programs.
The Windows API, informally WinAPI, is Microsoft's core set of application programming interfaces (APIs) available in the Microsoft Windows operating systems. The name Windows API collectively refers to several different platform implementations that are often referred to by their own names ; see the versions section. Almost all Windows programs interact with the Windows API. On the Windows NT line of operating systems, a small number use the Native API.
An embedded operating system is an operating system for embedded computer systems. Embedded operating systems are computer systems designed for a specific purpose, to increase functionality and reliability for achieving a specific task. Resource efficiency comes at the cost of losing some functionality or granularity that larger computer operating systems provide, including functions which may not be used by the specialized applications they run. Depending on the method used for multitasking, this type of OS is frequently considered to be a real-time operating system, or RTOS. Embedded systems are mostly used as Real-time operating systems. QNX, WinCE, and VxWorks are the most widely used embedded operating systems today.
An application program is a computer program designed to carry out a specific task other than one relating to the operation of the computer itself, typically to be used by end-users. Word processors, media players, and accounting software are examples. The collective noun refers to all applications collectively. The other principal classifications of software are system software, relating to the operation of the computer, and utility software ("utilities").
XNU is the computer operating system (OS) kernel developed at Apple Inc. since December 1996 for use in the Mac OS X operating system and released as free and open-source software as part of the Darwin OS, which is the basis for the Apple TV Software, iOS, iPadOS, watchOS, and tvOS OSes. XNU is an abbreviation of X is Not Unix.
In machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). The general task of pattern analysis is to find and study general types of relations in datasets. For many algorithms that solve these tasks, the data in raw representation have to be explicitly transformed into feature vector representations via a user-specified feature map: in contrast, kernel methods require only a user-specified kernel, i.e., a similarity function over pairs of data points in raw representation.
Semantic neural network (SNN) is based on John von Neumann's neural network [von Neumann, 1966] and Nikolai Amosov M-Network. There are limitations to a link topology for the von Neumann’s network but SNN accept a case without these limitations. Only logical values can be processed, but SNN accept that fuzzy values can be processed too. All neurons into the von Neumann network are synchronized by tacts. For further use of self-synchronizing circuit technique SNN accepts neurons can be self-running or synchronized.
Neural network software is used to simulate, research, develop, and apply artificial neural networks, software concepts adapted from biological neural networks, and in some cases, a wider array of adaptive systems such as artificial intelligence and machine learning.
Spiking neural networks (SNNs) are artificial neural networks that more closely mimic natural neural networks. In addition to neuronal and synaptic state, SNNs incorporate the concept of time into their operating model. The idea is that neurons in the SNN do not transmit information at each propagation cycle, but rather transmit information only when a membrane potential – an intrinsic quality of the neuron related to its membrane electrical charge – reaches a specific value, called the threshold. When the membrane potential reaches the threshold, the neuron fires, and generates a signal that travels to other neurons which, in turn, increase or decrease their potentials in response to this signal. A neuron model that fires at the moment of threshold crossing is also called a spiking neuron model.
Intel oneAPI Math Kernel Library, formerly Intel Math Kernel Library, is a library of optimized math routines for science, engineering, and financial applications. Core math functions include BLAS, LAPACK, ScaLAPACK, sparse solvers, fast Fourier transforms, and vector math.
There are many types of artificial neural networks (ANN).
NEST is a simulation software for spiking neural network models, including large-scale neuronal networks. NEST was initially developed by Markus Diesmann and Marc-Oliver Gewaltig and is now developed and maintained by the NEST Initiative.
In deep learning, a convolutional neural network is a class of artificial neural network, most commonly applied to analyze visual imagery. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on the shared-weight architecture of the convolution kernels or filters that slide along input features and provide translation equivariant responses known as feature maps. Counter-intuitively, most convolutional neural networks are only equivariant, as opposed to invariant, to translation. They have applications in image and video recognition, recommender systems, image classification, image segmentation, medical image analysis, natural language processing, brain-computer interfaces, and financial time series.
Linux kernel-based operating systems have been widely adopted in a very wide range of uses. All the advantages and benefits of free and open-source software apply to the Linux kernel, and to most of the rest of the system software.
Keras is an open-source software library that provides a Python interface for artificial neural networks. Keras acts as an interface for the TensorFlow library.
The following outline is provided as an overview of and topical guide to machine learning. Machine learning is a subfield of soft computing within computer science that evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a "field of study that gives computers the ability to learn without being explicitly programmed". Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from an example training set of input observations in order to make data-driven predictions or decisions expressed as outputs, rather than following strictly static program instructions.
Caffe is a deep learning framework, originally developed at University of California, Berkeley. It is open source, under a BSD license. It is written in C++, with a Python interface.
WireGuard is a communication protocol and free and open-source software that implements encrypted virtual private networks (VPNs), and was designed with the goals of ease of use, high speed performance, and low attack surface. It aims for better performance and more power than IPsec and OpenVPN, two common tunneling protocols. The WireGuard protocol passes traffic over UDP.
