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Showing 86 open source projects for "using"
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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Find Hidden Risks in Windows Task SchedulerWindows Task Scheduler might be hiding critical failures. Download the free JAMS diagnostic tool to uncover problems before they impact production—get a color-coded risk report with clear remediation steps in minutes.
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TensorFlow.js
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. ... -
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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. -
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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. -
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Laravel MongoDB
MongoDB based eloquent model and Query builder for Laravel
...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. -
Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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The GR module for Julia
Plotting for Julia based on GR
...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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statsmodels
Statsmodels, statistical modeling and econometrics in Python
...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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Constructs
Define composable configuration models through code
...Constructs are often used to represent the desired state of cloud applications. For example, in the AWS CDK, which is used to define the desired state for AWS infrastructure using CloudFormation, the lowest-level construct represents a resource definition in a CloudFormation template. These resources are composed to represent higher-level logical units of a cloud application, etc. -
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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... -
Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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OrientDB
DBMS supporting graph, document, full-text and geospatial models
...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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PlantUml allows to quickly create some UML diagram using a simple textual description language.
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Sparx' EA - MDG for TRAK
MDG for Sparx' Enterprise Architect to Create TRAK arch. descriptions
Custom add-in (MDG technology) for Sparx Systems Enterprise Architect UML modelling tool (https://sparxsystems.com/products/ea/index.html) to create architecture descriptions using TRAK https://sf.net/projects/trak Provides: - the set of TRAK views that can be represented using UML and SysML . Each view display a custom toolbox palette with the objects and relationships that are needed for that TRAK view - relationships can be made directly from the objects on a view using the Quicklink feature which presents the allowed relationship(s) by TRAK between the pair of objects selected - a custom set of searches. ... -
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Xtu
Xtu is a framework for implementing Platform specific xUML models
Xtu is a support framework for implementing Platform specific models (PSM) using the xUML methodology. xUML is a formalized methodology for Model based systems engineering (MBSE) targeted at SW and HW development. Xtu implements the xUML elements Domains, Bridges, Signals, Classes, States, Events & Finite state machines. Xtu targets C++11 & STL compatible PSMs. -
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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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TRAK UML Profile
Implementation of TRAK enterprise architecture framework as UML profil
UML (TRAK) and SysML (TRAK_SYSML) profiles for the TRAK open source architecture framework that provides the objects and relationships needed for implementation of TRAK in a UML enterprise architecture modelling tool. TRAK is a general systems enterprise architecture framework based on MODAF. -
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TRAK Viewpoints
Specifications for TRAK architecture views
...The triples that address each concern are defined in the TRAK metamodel (https://sf.net/p/trakmetamodel). The mapping between metamodel triple and architecture viewpoint is held with a Neo4J graph model (https://doi.org/10.1002/eng2.12168) and defined using (more) architecture viewpoints (https://www.researchgate.net/publication/335176248_Architecture_Description_Viewpoints_Metamodel_Description_Implementation_and_Model_Changes). The minimal process is defined in the overall TRAK specification (https://sf.net/p/trak) -
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MELO
Machine Executable Language Ontology (MELO)
This project is intended to fill the gap between the semantic web and the mainstream of software engineering, especially to integrate the semantic web with programming languages, and find an ontological representation of programming languages, including abstract syntax code execution, and global interoperability in execution environments. The machine executable language is modelled in OWL 2 DL using OWL API in C++ developed in this project. -
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M2SQL
Replicate your Mumps Globals into Relational Data Base
...Once mapping is completed you will able to replicate all the Mumps data into Target Relation database such as SQLITE or MYSQL. Normally you will do the replication process once a day while system is silent. This will give you a Relational Replication for Reporting or Business Analysis using industry standard tools. If you have a huge amount of data on your Mumps Globals you can choose an alternative mechanism in which only changes will be replicated to the target relational database and reflected almost immediately . The tool is a set of Mumps Routines and globals written on top of Intersystem IRIS , but using only pure Ansi standard Mumps . -
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TensorFlow.js models
Pretrained models for TensorFlow.js
...You can run the unit tests for any of the models by running "yarn test" inside a directory. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Build and train models directly in JavaScript using flexible and intuitive APIs. Develop ML models in JavaScript, and use ML directly in the browser or in Node.js. -
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
...They have the familiar Jupyter and JuypterLab interfaces that work well for single users, or small teams where users are also administrators. Advanced users also use SageMaker solely with the AWS CLI and Python scripts using boto3 and/or the SageMaker Python SDK. -
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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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USE is a system for the specification and validation of information systems based on a subset of the Unified Modeling Language (UML) and the Object Constraint Language (OCL). Please report any encountered bugs using the ticket system. The USE documentation can be found on the project homepage linked below. Downloads for the most popular plugins can be found here: http://sourceforge.net/projects/useocl/files/Plugins/
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PyText
A natural language modeling framework based 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 ship them at scale. Distributed-training support built on the new C10d backend in PyTorch 1.0. Mixed precision training support through APEX (trains faster with less GPU memory on NVIDIA Tensor Cores). ... -
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SageMaker Chainer Containers
Docker container for running Chainer scripts to train and host Chainer
...The Docker images, used to run training & inference jobs, are built from both corresponding "base" and "final" Dockerfiles. The "base" Dockerfile encompasses the installation of the framework and all of the dependencies needed. All "final" Dockerfiles build images using base images that use the tagging scheme. -
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The object-oriented modeling tool enables you to design and store diagrams (included in the ICONIX design process) in text and graphics, analyze the contents of diagrams, and create project reports. Diagrams are defined using a simple and intuitive language PlantUML. For the full operation of the application, graphviz is required. Link: https://graphviz.org/ Report an error or suggest an improvement: https://bitbucket.org/rrrfer-admin/uchebnaia-sreda-proektirovaniia/issues?status=new&status=open Ask a question and get advice: https://github.com/topics/forum About PlantUML: https://plantuml.com/
