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Showing 54 open source projects for "linux iso build"
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end. Migrate from on-prem or other clouds with free migration tools.
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Push Code. Get a Production URL. Done.Skip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Laravel MongoDB
MongoDB based eloquent model and Query builder for Laravel
This package adds functionalities to the Eloquent model and Query builder for MongoDB, using the original Laravel API. This library extends the original Laravel classes, so it uses exactly the same methods. Make sure you have the MongoDB PHP driver installed. In case your Laravel version does NOT autoload the packages, add the service provider to config/app.php. For usage with Lumen, add the service provider in bootstrap/app.php. In this file, you will also need to enable Eloquent. You must... -
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PyMC3
Probabilistic programming in Python
PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable... -
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TensorFlow.js
TensorFlow.js is a library for machine learning in JavaScript
TensorFlow.js is a library for machine learning in JavaScript. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Retrain pre-existing ML models using your own data. Build and train models directly in JavaScript using flexible and intuitive APIs. Tensors are the core datastructure of TensorFlow.js They are a generalization of vectors and matrices to... -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference,... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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ECLiPSe CLP
ECLiPSe Constraint Logic Programming System
The ECLiPSe Constraint Logic Programming System is designed for solving combinatorial optimization problems, for the development of new constraint solver technology and their hybrids, and for the teaching of modelling, solving and search techniques. -
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Extracts dependencies and OO metrics from Java class files produced by most Java compilers. Computes API differences between versions. No source needed. Includes both Swing and command-line interfaces, with XSL stylesheets for formatting output.
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DAE Tools Project
Object-oriented equation-based modelling and optimisation software
DAE Tools is a cross-platform equation-based object-oriented modelling, simulation and optimisation software. It is not a modelling language nor a collection of numerical libraries but rather a higher level structure – an architectural design of interdependent software components providing an API for: - Model development/specification - Activities on developed models, such as simulation, optimisation, sensitivity analysis and parameter estimation - Processing of the results, such as... -
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TRAK Viewpoints
Specifications for TRAK architecture views
The architecture viewpoints (specifications for architecture views iaw ISO 42010) for TRAK. TRAK is a general systems-thinkers'/system engineering enterprise architecture framework. It is simple, user-friendly, pragmatic and not limited to IT. 100% triple-centric and semantically-sound. Defines a total of 24 viewpoints. The ones needed are selected by taking the task sponsor's concerns and matching them to the typical concerns that each TRAK viewpoint addresses. The triples that address... -
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Java 2D & 3D visual entity relationship design & modeling (ERD,SQL) for Oracle,MSSQL,Postgres,MySQL,...,Database change&dictionary management, Swing Data Binding, Apache FOP Renderer for dot matrix printers,Sparx Enterprise Architect Reports + more
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Go From Idea to Deployed AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
DeepCTR-Torch is an easy-to-use, Modular and Extendible package of deep-learning-based CTR models along with lots of core components layers that can be used to build your own custom model easily.It is compatible with PyTorch.You can use any complex model with model.fit() and model.predict(). With the great success of deep learning, DNN-based techniques have been widely used in CTR estimation tasks. The data in the CTR estimation task usually includes high sparse,high cardinality categorical... -
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TensorFlow.js models
Pretrained models for TensorFlow.js
This repository hosts a set of pre-trained models that have been ported to TensorFlow.js. The models are hosted on NPM and unpkg so they can be used in any project out of the box. They can be used directly or used in a transfer learning setting with TensorFlow.js. To find out about APIs for models, look at the README in each of the respective directories. In general, we try to hide tensors so the API can be used by non-machine learning experts. New models should have a test NPM script. You... -
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
Welcome to Amazon SageMaker. This projects highlights example Jupyter notebooks for a variety of machine learning use cases that you can run in SageMaker. If you’re new to SageMaker we recommend starting with more feature-rich SageMaker Studio. It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies... -
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EiffelStudio is an Integrated Development Environment (IDE) that provides comprehensive facilities to programmers. It offers a comprehensive suite of tools that enable programmers to produce correct, reliable, and maintainable software while keeping control of the development process. If you want to create fast, robust, scalable applications, then EiffelStudio™ will offer you a cost-effective solution. Imagine being able to model your system as you think – capturing your requirements and...
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PyText
A natural language modeling framework based on PyTorch
PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly... -
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SageMaker Chainer Containers
Docker container for running Chainer scripts to train and host Chainer
SageMaker Chainer Containers is an open-source library for making the Chainer framework run on Amazon SageMaker. This repository also contains Dockerfiles which install this library, Chainer, and dependencies for building SageMaker Chainer images. Amazon SageMaker utilizes Docker containers to run all training jobs & inference endpoints. The Docker images are built from the Dockerfiles specified in Docker/. The Docker files are grouped based on Chainer version and separated based on Python... -
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setupdocx
Multidocument automation by templates - for sphinx, mkdocs, epydoc ...
The ‘setupdocx‘ provides a control layer for continuous documentation by the simplified creation, packaging, and installation of documentation. The provided commands are distributed as entry points and optional base classes for further customization into 'setup.py' - setuptools / distutils. Manages arbitrary document templates for the supported builder, supports multiple builds with arbitrary document layouts, designs, and patched contents. The current release supports the following... -
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JSDAI is a toolkit for STEP (ISO 10303), the STandard for the Exchange of Product Model data, that enables linking of CAD, CAM, PDM, PLM, CAx systems. JSDAI supports the development of Express data models (ISO 10303-11) and their implementation in Java.
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DRAKON Editor
A free cross-platform editor for the DRAKON visual language.
DRAKON is a diagram language developed within the Russian space program. Its primary objective is presenting complex software systems in a way which is easy to understand by humans. DRAKON's motto: took a glance - understood at once. DRAKON Editor helps software architects, quality specialists and developers. Architects and quality assurers can express a high-level view of how their product works. DRAKON serves them to explain the dynamics of a software system. Software engineers can use... -
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The FXL Project Eclipse Plugin leverages the integration of DSLs, (meta-) modeling approaches, code generation and the development of software configuration tools (sw-component-configuration).
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SEPIA: Security-oriented PN Framework
Petri net framework for security related modeling and reasoning.
...SEPIA builds upon TOVAL (http://sourceforge.net/p/toval), JAGAL (http://sourceforge.net/p/jagal) and SEWOL (https://sourceforge.net/projects/jawl/). To use SEPIA, make sure these libraries are on the build path. SEPIA encloses the Multi Schema Validator (https://msv.java.net/) and isorelax (http://iso-relax.sourceforge.net/) The documentation can be found under http://doku.telematik.uni-freiburg.de/sepia. -
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JAGAL: Java Graph Library
Java graph library
JAGAL provides implementations for directed graphs (weighted and unweighted) and varoius types of transition systems as well as utils for graph traversal and modification. JAGAL builds upon the Java library TOVAL (located at http://sourceforge.net/p/toval). To use JAGAL, make sure the TOVAL library is on the build path. This library uses and encloses jGraphX (https://github.com/jgraph/jgraphx). A documentation for JAGAL can be found under http://doku.telematik.uni-freiburg.de/jagal. -
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PROFACE is a User Interface Prototyper developed in Java. The objective of Proface is not code generation, but allow design/creation of interface idea with colors, buttons, texts, images, links and others.
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COORAD
Configurable Object Oriented Rapid Application Development system
COORAD is a classic LAMP/WAMP stack application. It let you quickly design web pages and configure actions to manage your data. Moreover, it let you self-generate pages/sections/actions/CSS/javascript by COORAD model objects and create your own models. So, you can share all your objects with the COORAD community and speed up your development. COORAD is a real general purpose application to build your own applications: simple sites, Content Managment Systems, Enterprise Resource Planners, etc. -
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SchemaForms is a toolkit for building HTML form from an XML data file and an XML-Schema specification. Supports basic data types (string, checkbox, enumeration,..) but is easily extensible to custom data types.
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This project will provide tools that leverage WS-CDL and Pi Calculus to build more robust Service Oriented Architectures (SOA). The tools are now released (and supported) through JBoss Tools (version > 3.2): http://www.jboss.org/tools
