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Kubeflow
Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes introduced by Google. The different stages in a typical machine learning lifecycle are represented with different software components in Kubeflow, including model development ''( Kubeflow Notebooks)'', model training ''( Kubeflow Pipelines'','' Kubeflow Training Operator)'', model serving ''( KServe)'', and automated machine learning ''(Katib)''. Each component of Kubeflow can be deployed separately, and it is not a requirement to deploy every component. History The Kubeflow project was first announced at '' KubeCon + CloudNativeCon North America 2017'' by Google engineers David Aronchick, Jeremy Lewi, and Vishnu Kannan to address a perceived lack of flexible options for building production-ready machine learning systems. The project has also stated it began as a way for Google to open-source how they ran TensorFlow internally. The first release of Kubeflow (Kubeflow 0.1) was announced at ''K ...
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Kubeflow Training Operator
Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes introduced by Google. The different stages in a typical machine learning lifecycle are represented with different software components in Kubeflow, including model development ''( Kubeflow Notebooks)'', model training ''( Kubeflow Pipelines'','' Kubeflow Training Operator)'', model serving ''( KServe)'', and automated machine learning ''(Katib)''. Each component of Kubeflow can be deployed separately, and it is not a requirement to deploy every component. History The Kubeflow project was first announced at '' KubeCon + CloudNativeCon North America 2017'' by Google engineers David Aronchick, Jeremy Lewi, and Vishnu Kannan to address a perceived lack of flexible options for building production-ready machine learning systems. The project has also stated it began as a way for Google to open-source how they ran TensorFlow internally. The first release of Kubeflow (Kubeflow 0.1) was announced at ''K ...
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Kubeflow Pipelines
Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes introduced by Google. The different stages in a typical machine learning lifecycle are represented with different software components in Kubeflow, including model development ''( Kubeflow Notebooks)'', model training ''( Kubeflow Pipelines'','' Kubeflow Training Operator)'', model serving ''( KServe)'', and automated machine learning ''(Katib)''. Each component of Kubeflow can be deployed separately, and it is not a requirement to deploy every component. History The Kubeflow project was first announced at '' KubeCon + CloudNativeCon North America 2017'' by Google engineers David Aronchick, Jeremy Lewi, and Vishnu Kannan to address a perceived lack of flexible options for building production-ready machine learning systems. The project has also stated it began as a way for Google to open-source how they ran TensorFlow internally. The first release of Kubeflow (Kubeflow 0.1) was announced at ''Ku ...
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Kubeflow Notebooks
Kubeflow is an open-source platform for machine learning and MLOps on Kubernetes introduced by Google. The different stages in a typical machine learning lifecycle are represented with different software components in Kubeflow, including model development ''( Kubeflow Notebooks)'', model training ''(Kubeflow Pipelines'','' Kubeflow Training Operator)'', model serving ''( KServe)'', and automated machine learning ''(Katib)''. Each component of Kubeflow can be deployed separately, and it is not a requirement to deploy every component. History The Kubeflow project was first announced at '' KubeCon + CloudNativeCon North America 2017'' by Google engineers David Aronchick, Jeremy Lewi, and Vishnu Kannan to address a perceived lack of flexible options for building production-ready machine learning systems. The project has also stated it began as a way for Google to open-source how they ran TensorFlow internally. The first release of Kubeflow (Kubeflow 0.1) was announced at ''Kub ...
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TensorFlow
TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep 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 TensorFlow was developed by the Google Brain team for internal Google use in research and production. The initial version was released under the Apache License 2.0 in 2015. Google released the updated version of TensorFlow, named TensorFlow 2.0, in September 2019. TensorFlow can be used in a wide variety of programming languages, including Python, JavaScript, C++, and Java. This flexibility lends itself to a range of applications in many different sectors. History DistBelief Starting in 2011, Google Brain built DistBelief as a proprietary machine learning system based on deep learning neural n ...
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Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ...
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Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ...
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RStudio
RStudio is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser. Licensing model The RStudio integrated development environment (IDE) is available with the GNU Affero General Public License version 3. The AGPL v3 is an open source license that guarantees the freedom to share the code. RStudio Desktop and RStudio Server are both available in free and fee-based (commercial) editions. OS support depends on the format/edition of the IDE. Prepackaged distributions of RStudio Desktop are available for Windows, macOS, and Linux. RStudio Server and Server Pro run on Debian, Ubuntu, Red Hat Linux, CentOS, openSUSE and SLES. Overview and History The RStudio IDE is partly written in the C++ programming language and uses the Qt framework for its graphical ...
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Visual Studio Code
Visual Studio Code, also commonly referred to as VS Code, is a source-code editor made by Microsoft with the Electron Framework, for Windows, Linux and macOS. Features include support for debugging, syntax highlighting, intelligent code completion, snippets, code refactoring, and embedded Git. Users can change the theme, keyboard shortcuts, preferences, and install extensions that add additional functionality. In the Stack Overflow 2021 Developer Survey, Visual Studio Code was ranked the most popular developer environment tool among 82,000 respondents, with 70% reporting that they use it. History Visual Studio Code was first announced on April 29, 2015, by Microsoft at the 2015 Build conference. A preview build was released shortly thereafter. On November 18, 2015, the source of Visual Studio Code was released under the MIT License, and made available on GitHub. Extension support was also announced. On April 14, 2016, Visual Studio Code graduated from the public preview ...
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Katib
A katib ( ar, كَاتِب, ''kātib'') is a writer, scribe, or secretary in the Arabic-speaking world, Persian World, and other Islamic areas as far as India. In North Africa, the local pronunciation of the term also causes it to be written ketib. Duties comprised reading and writing correspondence, issue instructions at the command of the person in charge and archiving documentation. The word comes probably from Arabic kitāb (book), and perhaps imported from the Northern Aramaic neighbors of the Arabs. It is a pre-Islamic concept, encountered in the work of ancient Arab poets. The art of writing, although present in all part of Arabia, was apparently accomplishment of the few. Among the Companions of Medina, about ten are mentioned as katibs. With the embrace of Islam, the office of katib became a post of great honor. By this time, on the model of the Persian chancellery, a complicated system of government offices had developed, each branch of governmental, religious, civic, or ...
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Jupyter Notebook
Project Jupyter () is a project with goals to develop open-source software, open standards, and services for interactive computing across multiple programming languages. It was spun off from IPython in 2014 by Fernando Pérez and Brian Granger. Project Jupyter's name is a reference to the three core programming languages supported by Jupyter, which are Julia, Python and R. Its name and logo are an homage to Galileo's discovery of the moons of Jupiter, as documented in notebooks attributed to Galileo. Project Jupyter has developed and supported the interactive computing products Jupyter Notebook, JupyterHub, and JupyterLab. Jupyter is financially sponsored by NumFOCUS. History The first version of Notebooks for IPython was released in 2011 by a team including Fernando Pérez, Brian Granger, and Min Ragan-Kelley. In 2014, Pérez announced a spin-off project from IPython called Project Jupyter. IPython continues to exist as a Python shell and a kernel for Jupyter, while th ...
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GitHub
GitHub, Inc. () is an Internet hosting service for software development and version control using Git. 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. As of June 2022, GitHub reported having over 83 million developers and more than 200 million repositories, including at least 28 million public repositories. It is the largest source code host . History GitHub.com Development of the GitHub.com platform began on October 19, 2007. The site was launched in April 2008 by Tom Preston-Werner, Chris Wanstrath, P. J. Hyett and Scott Chacon after it had been made available for a few months prior as a beta release. GitHub has an annual keynote called GitHub Universe. Organizational ...
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Software Portability
A computer program is said to be portable if there is very low effort required to make it run on different platforms. The pre-requirement for portability is the generalized abstraction between the application logic and system interfaces. When software with the same functionality is produced for several computing platforms, portability is the key issue for development cost reduction. Strategies for portability Software portability may involve: * Transferring installed program files to another computer of basically the same architecture. * Reinstalling a program from distribution files on another computer of basically the same architecture. * Building executable programs for different platforms from source code; this is what is usually understood by "porting". Similar systems When operating systems of the same family are installed on two computers with processors with similar instruction sets it is often possible to transfer the files implementing program files between the ...
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