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Systems Design
The basic study of system design is the understanding of component parts and their subsequent interaction with one another. Systems design has appeared in a variety of fields, including sustainability, computer/software architecture, and sociology. Product Development If the broader topic of product development "blends the perspective of marketing, design, and manufacturing into a single approach to product development," then design is the act of taking the marketing information and creating the design of the product to be manufactured. Thus in product development, systems design involves the process of defining and developing systems, such as interfaces and data, for an electronic control system to satisfy specified requirements. Systems design could be seen as the application of systems theory to product development. There is some overlap with the disciplines of systems analysis, systems architecture and systems engineering. Physical design The physical design relates to t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data
Data ( , ) are a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data are usually organized into structures such as tables that provide additional context and meaning, and may themselves be used as data in larger structures. Data may be used as variables in a computational process. Data may represent abstract ideas or concrete measurements. Data are commonly used in scientific research, economics, and virtually every other form of human organizational activity. Examples of data sets include price indices (such as the consumer price index), unemployment rates, literacy rates, and census data. In this context, data represent the raw facts and figures from which useful information can be extracted. Data are collected using technique ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recommender System
A recommender system (RecSys), or a recommendation system (sometimes replacing ''system'' with terms such as ''platform'', ''engine'', or ''algorithm'') and sometimes only called "the algorithm" or "algorithm", is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user. Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer. Modern recommendation systems such as those used on large social media sites make extensive use of AI, machine learning and related techniques to learn the behavior and preferences of each user and categorize content to tailor their feed individually. Typically, the suggestions refer to various decision-making processes, such as what product to purchase, what music to listen to, or what online news to read. Recommender systems are used in a variety of areas, with commonly recognised ex ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Architectural Pattern (computer Science)
Software architecture pattern is a reusable, proven solution to a specific, recurring problem focused on architectural design challenges, which can be applied within various architectural styles. Examples Some examples of architectural patterns: * Publish–subscribe pattern * Message broker See also * List of software architecture styles and patterns * Process Driven Messaging Service * Enterprise architecture Enterprise architecture (EA) is a business function concerned with the structures and behaviours of a business, especially business roles and processes that create and use business data. The international definition according to the Federation of ... * Common layers in an information system logical architecture References Bibliography * * * {{Design Patterns patterns Software design patterns ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Arcadia (engineering)
ARCADIA (Architecture Analysis & Design Integrated Approach) is a Systems engineering, system and Software engineering, software architecture engineering method based on architecture-centric and model-driven engineering activities. History In the development cycle of a system, former practices focused more on the definition of requirements, their allocation to each component of the system component and associated traceability. Current approaches rather focus on Functional_design, functional analysis, Systems design, system design, justification of architectural choices, and verification steps. In addition, the design takes into account not only the Function model, functional point of view, but also other points of view, which affect the definition and breakdown of the system. For example, Constraint (computer-aided design), constraints relating to system integration, Product lining, product line management, safety, performance and Logical possibility, feasibility. Systems engine ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MLOps
MLOps or ML Ops is a paradigm that aims to deploy and maintain machine learning models in production reliably and efficiently. It bridges the gap betweemachine learning developmentand production operations, ensuring that models are robust, scalable, and aligned with business goals. The word is a compound of "machine learning" and the continuous delivery practice (CI/CD) of DevOps in the software field. Machine learning models are tested and developed in isolated experimental systems. When an algorithm is ready to be launched, MLOps is practiced between Data Scientists, DevOps, and Machine Learning engineers to transition the algorithm to production systems. Similar to DevOps or DataOps approaches, MLOps seeks to increase automation and improve the quality of production models, while also focusing on business and regulatory requirements. While MLOps started as a set of best practices, it is slowly evolving into an independent approach to ML lifecycle management. MLOps applies to the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Concept Drift
In predictive analytics, data science, machine learning and related fields, concept drift or drift is an evolution of data that invalidates the data model. It happens when the statistical properties of the target variable, which the model is trying to predict, change over time in unforeseen ways. This causes problems because the predictions become less accurate as time passes. Drift detection and drift adaptation are of paramount importance in the fields that involve dynamically changing data and data models. Predictive model decay In machine learning and predictive analytics this drift phenomenon is called concept drift. In machine learning, a common element of a data model are the statistical properties, such as probability distribution of the actual data. If they deviate from the statistical properties of the training data set, then the learned predictions may become invalid, if the drift is not addressed. Data configuration decay Another important area is software engineering, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Kubernetes
Kubernetes (), also known as K8s is an open-source software, open-source OS-level virtualization, container orchestration (computing), orchestration system for automating software deployment, scaling, and management. Originally designed by Google, the project is now maintained by a worldwide community of contributors, and the trademark is held by the Cloud Native Computing Foundation. The name ''Kubernetes'' originates from the Greek language, Greek κυβερνήτης (kubernḗtēs), meaning 'governor', 'helmsman' or 'pilot'. ''Kubernetes'' is often abbreviated as ''K8s'', counting the eight letters between the ''K'' and the ''s'' (a numeronym). Kubernetes assembles one or more computers, either virtual machines or bare machine, bare metal, into a Computer cluster, cluster which can run workloads in containers. It works with various container runtimes, such as containerd and Cloud Native Computing Foundation#CRI-O, CRI-O. Its suitability for running and managing workloads of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Docker (software)
Docker is a set of platform as a service (PaaS) products that use OS-level virtualization to deliver software in packages called ''containers''. The service has both free and premium tiers. The software that hosts the containers is called Docker Engine. It was first released in 2013 and is developed by Docker, Inc. Docker is a tool that is used to automate the deployment of applications in lightweight containers so that applications can work efficiently in different environments in isolation. Background Containers are isolated from one another and bundle their own software, libraries and configuration files; they can communicate with each other through well-defined channels. Because all of the containers share the services of a single operating system kernel, they use fewer resources than virtual machines. Operation Docker can package an application and its dependencies in a virtual container that can run on any Linux, Windows, or macOS computer. This enables the appli ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PyTorch
PyTorch is a machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, originally developed by Meta AI and now part of the Linux Foundation umbrella. It is one of the most popular deep learning frameworks, alongside others such as TensorFlow, offering free and open-source software released under the modified BSD license. Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot, Uber's Pyro, Hugging Face's Transformers, and Catalyst. PyTorch provides two high-level features: * Tensor computing (like NumPy) with strong acceleration via graphics processing units (GPU) * Deep neural networks built on a tape-based automatic differentiation system History In 2001, Torch was written and released under a GPL license. It was a machine-learning li ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
TensorFlow
TensorFlow is a Library (computing), software library for machine learning and artificial intelligence. It can be used across a range of tasks, but is used mainly for Types of artificial neural networks#Training, training and Statistical inference, inference of Neural network (machine learning), neural networks. "It is machine learning software being used for various kinds of perceptual and language understanding tasks" – Jeffrey Dean, minute 0:47 / 2:17 from YouTube clip It is one of the most popular deep learning frameworks, alongside others such as PyTorch. It is free and open-source software released under the Apache License 2.0. It was developed by the Google Brain team for Google's internal use in research and production. The initial version was released under the Apache License 2.0 in 2015. Google released an updated version, TensorFlow 2.0, in September 2019. TensorFlow can be used in a wide variety of programming languages, including Python (programming language), P ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Neural Networks
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either Cell (biology), biological cells or signal pathways. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural networks. *In neuroscience, a ''biological neural network'' is a physical structure found in brains and complex nervous systems – a population of nerve cells connected by synapses. *In machine learning, an ''Neural network (machine learning), artificial neural network'' is a mathematical model used to approximate nonlinear functions. Artificial neural networks are used to solve artificial intelligence problems. In biology In the context of biology, a neural network is a population of biological neurons chemically connected to each other by synapses. A given neuron can be connected to hundreds of thousands of synapses. Each neuron sends and receives Electrochemistry, ele ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Decision Trees
A decision tree is a decision support system, decision support recursive partitioning structure that uses a Tree (graph theory), tree-like Causal model, model of decisions and their possible consequences, including probability, chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in Decision tree learning, machine learning. Overview A decision tree is a flowchart-like structure in which each internal node represents a test on an attribute (e.g. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, and each leaf node represents a class label (decision taken after computing all attributes). The paths from root to leaf represent classification rules. In decision analysis, a de ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
