Open Source Windows UML Tools
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UML Tools for Windows
View 1876 business solutionsBrowse free open source UML tools and projects for Windows below. Use the toggles on the left to filter open source UML tools by OS, license, language, programming language, and project status.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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PlantUml allows to quickly create some UML diagram using a simple textual description language.
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brModelo 3.2
ER Databese Model
Tool used to Database ER model Ferramenta para modelagem ER em bancos de dados. -
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StarUML is an open source project to develop fast, flexible, extensible, featureful, and freely-available UML/MDA platform running on Win32 platform. The goal is a compelling replacement of commercial UML tools such as RationalRose, Together and so on.
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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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Violet is a UML editor with these benefits: Very easy to learn and use. Draws nice-looking diagrams. Completely free. Cross-platform. Violet is intended for developers, students, teachers, and authors who need to produce simple UML diagrams quickly. Want to contribute ? Source code is hosted on github : https://github.com/violetumleditor/violetumleditor
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Mongoose
Elegant mongodb object modeling for node.js
Mongoose is a MongoDB object modeling tool that was built to answer the need for better ways to model your application data. It's designed to work in an asynchronous environment, providing a simple, straightforward approach to object modeling that skips out on the tedious tasks of writing MongoDB validation, casting and business logic boilerplate. Mongoose offers an uncomplicated schema-based solution, and comes with nifty features like type casting, validation, query building, and business logic hooks right out of the box. Mongoose also has a rich set of plugins made by the community and you can write your own to make Mongoose an even better solution for your needs. -
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The Whole Platform is a technology for engineering the production of software. We provide an Eclipse based Language Workbench for developing, manipulating and transforming languages using a model driven approach.
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NClass is a free tool to easily create UML class diagrams with full C# and Java language support.
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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 your thought processes with EiffelStudio. When ready to design, you build upon the model you just created, still with EiffelStudio. Then you implement with EiffelStudio. You never need to throw anything out and start over. You don’t need extra tools to go back and safely make changes in your architecture. Roundtrip engineering? It’s built in by design. Testing, metrics and productivity tools? They’re built in. EiffelStudio accommodates quickly and efficiently new thoughts and changes.
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No-Nonsense Code-to-Cloud Security for Devs | AikidoAikido provides a unified security platform for developers, combining 12 powerful scans like SAST, DAST, and CSPM. AI-driven AutoFix and AutoTriage streamline vulnerability management, while runtime protection blocks attacks.
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Yaoqiang BPMN Editor
an Open Source BPMN 2.0 / DMN 1.1 Modeler
Yaoqiang BPMN Editor is a graphical editor for business process diagrams, compliant with OMG specifications (BPMN 2.0 / DMN 1.1). -
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WhiteStarUML
UML modeling tool derived from StarUML compatible with Windows 7-10
WhiteStarUML is a fork of StarUML 5.0 providing a number of bug fixes and improving compatibility with modern operating systems. -
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The GR module for Julia
Plotting for Julia based on GR
This is the GR module for Julia. It places a Julia interface to GR, a universal framework for visualization applications. GR allows users to create high quality, engaging visualizations, everything from 2D graphs to complex 3D scenes. With this module simply type in Julia 'using gr', and you can instantly start calling functions in the GR framework API. GR is based on an implementation of a Graphical Kernel System (GKS) and OpenGL. As a self-contained system, integration into existing applications is quick and easy-- simply use a direct call from Julia with ccall syntax. -
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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 DRAKON Editor to build algorithms in Go, Java, Processing.org, D, C#, C, C++, Python, Tcl, Javascript, Erlang and Lua. -
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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, transforms etc. They've been tested for machine learning workloads on Amazon EC2, Amazon ECS and Amazon EKS services as well. This project is licensed under the Apache-2.0 License. Ensure you have access to an AWS account i.e. setup your environment such that awscli can access your account via either an IAM user or an IAM role. -
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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 potentially higher dimensions. Built on top of TensorFlow.js, the ml5.js library provides access to machine learning algorithms and models in the browser with a concise, approachable API. Comfortable with concepts like Tensors, Layers, Optimizers and Loss Functions (or willing to get comfortable with them)? TensorFlow.js provides flexible building blocks for neural network programming in JavaScript. -
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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 of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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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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A fast and reliable tool, written in Java 8, for generating professional UML sequence diagrams from text. Supports actors, con-/destructors, threads, broadcasts, notes, and fragments. Can serve as a Javadoc taglet. Exports PDF, (E)PS, SVG, PNG, ... The source code is hosted at http://github.com/sdedit/sdedit
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OrientDB
DBMS supporting graph, document, full-text and geospatial models
OrientDB is an Open Source Multi-Model NoSQL DBMS with the support of Native Graphs, Documents, Full-Text search, Reactivity, Geo-Spatial and Object Oriented concepts. It's written in Java and it's amazingly fast. No expensive run-time JOINs, connections are managed as persistent pointers between records. You can traverse thousands of records in no time. Supports schema-less, schema-full and schema-mixed modes. Has a strong security profiling system based on user, roles and predicate security and supports SQL amongst the query languages. Thanks to the SQL layer it's straightforward to use for people skilled in the Relational world. OrientDB adheres to the NoSQL movement even though it supports ACID Transactions and SQL as query language. In this way it's easy to start using it without having to learn too much new stuff. -
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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 in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets. -
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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 reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. Write a training script (eg. train.py). Define a container with a Dockerfile that includes the training script and any dependencies. -
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NOTE: The GROOVE codebase has moved to https://github.com/nl-utwente-groove
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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 features and some dense numerical features. Low-order Extractor learns feature interaction through product between vectors. Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction. High-order Extractor learns feature combination through complex neural network functions like MLP, Cross Net, etc. -
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Laravel Media Library
Associate files with Eloquent models
This package can associate all sorts of files with Eloquent models. It provides a simple, fluent API to work with. The Pro version of the package offers Blade, Vue and React components to handle uploads to the media library and to administer the content of a medialibrary collection. The storage of the files is handled by Laravel's Filesystem, so you can use any filesystem you like. Additionally the package can create image manipulations on images and pdfs that have been added in the media library. -
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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 however ensure that your call to $app->withEloquent(); is below where you have registered the MongodbServiceProvider. The service provider will register a MongoDB database extension with the original database manager. There is no need to register additional facades or objects. When using MongoDB connections, Laravel will automatically provide you with the corresponding MongoDB objects.
