CollaborationCollaboration (from Latin com- "with" + laborare "to labor", "to work") is the process of two or more people, entities or organizations working together to complete a task or achieve a goal. Collaboration is similar to cooperation. Most collaboration requires leadership, although the form of leadership can be social within a decentralized and egalitarian group. Teams that work collaboratively often access greater resources, recognition and rewards when facing competition for finite resources.
Mass collaborationMass collaboration is a form of collective action that occurs when large numbers of people work independently on a single project, often modular in its nature. Such projects typically take place on the internet using social software and computer-supported collaboration tools such as wiki technologies, which provide a potentially infinite hypertextual substrate within which the collaboration may be situated. Open source software such as Linux was developed via mass collaboration.
Competition (biology)Competition is an interaction between organisms or species in which both require a resource that is in limited supply (such as food, water, or territory). Competition lowers the fitness of both organisms involved since the presence of one of the organisms always reduces the amount of the resource available to the other. In the study of community ecology, competition within and between members of a species is an important biological interaction.
GitGit (gɪt) is a distributed version control system that tracks changes in any set of s, usually used for coordinating work among programmers who are collaboratively developing source code during software development. Its goals include speed, data integrity, and support for distributed, non-linear workflows (thousands of parallel branches running on different computers). Git was originally authored by Linus Torvalds in 2005 for development of the Linux kernel, with other kernel developers contributing to its initial development.
Nonlinear programmingIn mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints or the objective function are nonlinear. An optimization problem is one of calculation of the extrema (maxima, minima or stationary points) of an objective function over a set of unknown real variables and conditional to the satisfaction of a system of equalities and inequalities, collectively termed constraints. It is the sub-field of mathematical optimization that deals with problems that are not linear.
Automated machine learningAutomated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment. AutoML was proposed as an artificial intelligence-based solution to the growing challenge of applying machine learning. The high degree of automation in AutoML aims to allow non-experts to make use of machine learning models and techniques without requiring them to become experts in machine learning.
Generative adversarial networkA generative adversarial network (GAN) is a class of machine learning framework and a prominent framework for approaching generative AI. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate new data with the same statistics as the training set.
Repository (version control)In version control systems, a repository is a data structure that stores metadata for a set of files or directory structure. Depending on whether the version control system in use is distributed, like Git or Mercurial, or centralized, like Subversion, CVS, or Perforce, the whole set of information in the repository may be duplicated on every user's system or may be maintained on a single server. Some of the metadata that a repository contains includes, among other things, a historical record of changes in the repository, a set of commit objects, and a set of references to commit objects, called heads.
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
GitHubGitHub, Inc. (ˈgɪthʌb) is a platform and cloud-based service for software development and version control using Git, allowing developers to store and manage their code. It provides the distributed version control of Git plus access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. Headquartered in California, it has been a subsidiary of Microsoft since 2018. It is commonly used to host open source software development projects.
Interspecific competitionInterspecific competition, in ecology, is a form of competition in which individuals of different species compete for the same resources in an ecosystem (e.g. food or living space). This can be contrasted with mutualism, a type of symbiosis. Competition between members of the same species is called intraspecific competition. If a tree species in a dense forest grows taller than surrounding tree species, it is able to absorb more of the incoming sunlight.
Supervised learningSupervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal) train a model. The training data is processed, building a function that maps new data on expected output values. An optimal scenario will allow for the algorithm to correctly determine output values for unseen instances. This requires the learning algorithm to generalize from the training data to unseen situations in a "reasonable" way (see inductive bias).
