Search Results for "eclipse python uml"
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Showing 389 open source projects for "eclipse python uml"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
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PyDev is a Python Development Environment (Python IDE plugin for Eclipse). It features an editor with code completion, code analysis, refactoring, outline view, debugger, mark occurrences and other goodies - check http://pydev.org for more details). It's kept going by community contributions, so, if you think it's a worthy project, please contribute through http://pydev.org
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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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statsmodels
Statsmodels, statistical modeling and econometrics in Python
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests, and statistical data exploration. An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all... -
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torchvision
Datasets, transforms and models specific to Computer Vision
The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. We recommend Anaconda as Python package management system. Torchvision currently supports Pillow (default), Pillow-SIMD, which is a much faster drop-in replacement for Pillow with SIMD, if installed will be used as the default. Also, accimage, if installed can be activated by calling torchvision.set_image_backend('accimage'), libpng, which can be installed via... -
Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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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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Open tool platform for the cost effective rigorous development of dependable complex software systems services. This platform is based on the event-B formal method and provides natural support for refinement and mathematical proof.
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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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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
SageMaker Hugging Face Inference Toolkit is an open-source library for serving Transformers models on Amazon SageMaker. This library provides default pre-processing, predict and postprocessing for certain Transformers models and tasks. It utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. For the Dockerfiles used for building SageMaker Hugging Face Containers, see AWS Deep Learning Containers. The SageMaker Hugging... -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
Train machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and... -
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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,... -
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TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models... -
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Theia
Cloud & Desktop IDE Platform
Eclipse Theia is an open source extensible platform for developing multi-language Cloud and Desktop IDEs with state-of-the-art web technologies. If you’re not sure if you need a web version or a desktop version or both, Theia is the best solution. It can develop one IDE for both browsers and native desktop applications from a single source. Theia has a highly flexible architecture, allowing extenders and adopters to customize and extend every aspect of it. It supports VS code extensions,... -
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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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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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Gradle
Adaptable, fast automation for all
...Gradle has been designed to support build automation across multiple languages and platforms including Java, Scala, Android, Kotlin, C/C++, and Groovy, and is closely integrated with development tools and continuous integration servers including Eclipse, IntelliJ, and Jenkins. From mobile apps to microservices, from small startups to big enterprises, Gradle helps teams build, automate and deliver better software, faster. Write in Java, C++, Python or your language of choice. Package for deployment on any platform. Go monorepo or multi-repo. And rely on Gradle's unparalleled versatility to build it all. -
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JGraphT is a free Java class library that provides mathematical graph-theory objects and algorithms. JGraphT supports a rich gallery of graphs and is designed to be powerful, extensible, and easy to use.
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umple
The Umple Model-Oriented Programming Technology
Umple is technology for Model-Oriented Programming. It adds abstractions such as UML associations, attributes, and state machines to object-oriented programming languages such as Java, C++, PHP and Ruby. A developer can use Umple in one of several ways. They can start with a pure model, containing only classes, associations, attributes and state machines, and then gradually add methods in one of the base languages to the Umple code base. Alternatively a developer can start with a normal... -
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DocFetcher
Desktop search application
DocFetcher is an Open Source desktop search application: It allows you to search the contents of files on your computer. — You can think of it as Google for your local files. The application runs on Windows, Linux and Mac OS X. -
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PySchool
Installable / Portable Python Distribution for Everyone.
PySchool is a free and open-source Python distribution intended primarily for students who learn Python and data analysis, but it can also used by scientists, engineering, and data scientists. It includes more than 150 Python packages (full edition) including numpy, pandas, scipy, sympy, keras, scikit-learn, matplotlib, seaborn, beautifulsoup4... -
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geometry3d
A Python library for geometric objects in 3 dimentions
Implemented classes of 3d objects: * Vector3D * Point3D * Line3D * Plane3D * Ray3D * HalfPlane3D * HalfSpace3D * LineSegment3D Yet incompletely implemented classes: * Triangle3D * Disk3D (closed circle) * Union3D * Difference3D Each object has methods for finding its sizes, containing box or containing sphere. It finds intersection and distance or closest to another object part of itself. It also can tell if it contains the other object or is it contained by... -
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SQL DAL Maker
A generator of DTO, Model, and DAO classes to access relational DB
SQL DAL Maker is a generator of DTO, Model, and DAO classes to access relational databases. Target programming languages: PHP, Java, C++, Python, and Go. To generate the class, you declare it in XML meta-program. At the stage of code generation, the target database must exist and be available for JDBC connection. Generated code is being synchronized with the current database schema using "live" JDBC metadata. Written in Java. Implemented as plug-ins For Eclipse: https://marketplace.eclipse.org/content/sql-dal-maker For IntelliJ: https://plugins.jetbrains.com/plugin/7092 HOWTO install-update: http://sqldalmaker.sourceforge.net GitHub: https://github.com/panedrone/sqldalmaker Quick-Demo in mp4: https://github.com/panedrone/sqldalmaker/releases/tag/latest -
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SPELL
Satellite Procedure Execution Language and Library
SPELL is a framework composed of an integrated environment for the development and execution of satellite automated procedures. It is capable of running any procedure via different Ground Control System and for any spacecraft. The goal of SPELL is to have a powerful and readable automation language, which can be shared across Satellite Operators and Satellite Manufacturers. If we all use the same language, the cost and the risk associated with automated procedures will go down! SPELL... -
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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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Simulation of Urban MObility
SUMO is a microscopic, multi-modal traffic simulation.
SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation. The code and the issue tracker can be found at https://github.com/eclipse-sumo/sumo/ The documentation can be found at https://sumo.dlr.de/docs/
