Search Results for "model-builder"
Sort By:
Showing 218 open source projects for "model-builder"
View related business solutions-
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
-
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.
-
1
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. -
2
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 are suitable. ... -
3
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. ... -
4
SageMaker Hugging Face Inference Toolkit
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 Face Inference Toolkit implements various additional environment variables to simplify your deployment experience. The Hugging Face Inference Toolkit allows user to override the default methods of the HuggingFaceHandlerService. ... -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
5
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. -
6
SageMaker Training Toolkit
Train machine learning models within Docker containers
...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. ... -
7
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. ... -
8
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... -
9
redux-saga
An alternative side effect model library for Redux applications
redux-saga is a library that aims to make application side effects (i.e. asynchronous things like data fetching and impure things like accessing the browser cache) easier to manage, more efficient to execute, easy to test, and better at handling failures. The mental model is that a saga is like a separate thread in your application that's solely responsible for side effects. redux-saga is a redux middleware, which means this thread can be started, paused and cancelled from the main application with normal redux actions, it has access to the full redux application state and it can dispatch redux actions as well. ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
10
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. -
11
statsmodels
Statsmodels, statistical modeling and econometrics in Python
...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. -
12
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 conda conda install libpng or any of the package managers for debian-based and RHEL-based Linux distributions, and libjpeg, which can be installed via conda conda install jpeg or any of the package managers for debian-based and RHEL-based Linux distributions. ... -
13
MJExtension
A conversion framework between JSON and model
A fast, convenient and nonintrusive conversion framework between JSON and model. Dictionary-to-model framework with fast conversion speed and easy to use. A large number of unit tests have been carried out on various commonly used data scenarios. MJExtension is an ultra-lightweight framework that converts between dictionaries and models. Coding all properties of a model with only one line of code. Coding (archiving and unarchiving) of all attributes of the model can be achieved with just one line of code. ... -
14
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. -
15
NOTE: The GROOVE codebase has moved to https://github.com/nl-utwente-groove
-
16
DAE Tools Project
Object-oriented equation-based modelling 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 plotting and exporting to various file formats - Report generation - Code generation, co-simulation and model exchange The following class of problems can be solved by DAE Tools: - Initial value problems of implicit form - Index-1 DAE systems - With lumped or distributed parameters - Steady-state or dynamic - Continuous with some elements of event-driven systems -
17
Sparx' EA - MDG for TRAK
MDG for Sparx' Enterprise Architect to Create TRAK arch. descriptions
...When run these will list objects of a particular type (e.g. all Systems, all Enterprise Goals), potential quality problems (e.g. diagrams and objects without any description, objects not linked to any other), things of interest (e.g. open, closed concerns) and view-like results e.g. all structural relationships in the solution - model views to list object -
18
odaba
ODABA is an terminology-oriented database management system and develo
ODABA is an terminology-oriented database management system (TODBMS) on a high conceptual level. It provides a number of enhanced features based on natural language analysis. Terminology orientation allows designing user oriented data models. Enhanced event model and Active Data Link technology support rapid development of GUI applications. Several development, documentation, test and analyzing tools are provided in order to support developers and administrators. .NET interface and a powerful object-orjented script language (OSI) improve development efficiency. -
19
Optimizer_sovkov
Constructing and optimizing general mathematical and physical models
...The convenient visual interface and the detailed manuals are provided. The main benefit of the package is its capability to construct models of any level of complexity in a block-by-block manner. Elementary model blocks can be collected in libraries, and we have already written many such library programs. Many of these programs are already available along with the main package. Currently, the main focus of these is computational quantum mechanics, analysis and simulation of molecular spectra, and general-purpose approximants. The package provides the most reliable modern strategies for linear and non-linear model optimization, regularization, and hypothesis tests. ... -
20
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) -
21
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. -
22
UML and SysML with TRAK
Annotate/link UML and SysML diagrams with TRAK AF elements
Provides UML (SysML) profiles and a MDG for Sparx Systems EA to allow you to add TRAK elements to standard UML and SysML diagrams and link to TRAK architecture descriptions. Links TRAK Resource to UseCase as subject or collaborator and to States exhibited. -
23
ConceptBase.cc
A Database System for Metamodeling and Method Engineering
ConceptBase.cc is a multi-user deductive and object-oriented database system for metamodeling and method engineering. Includes a graphical client that builds upon the logic-based features of the ConceptBase.cc server. The data model is O-Telos. ConceptBase.cc can represent information at the data level (example data, traces of process executions etc.), the class level (schemas, process definitions etc.), the metaclass level (constructs of modeling languages), the meta-metaclass level (constructs for defining modeling languages), and so forth. ConceptBase.cc is developed by the ConceptBase Team at University of Skövde (HIS). ... -
24
smclarify
Fairness aware machine learning. Bias detection and mitigation
...A facet can have value(s) that designates that sample as "sensitive". Bias detection and mitigation for datasets and models. The label is a column or feature which is the target for training a machine learning model. The label can have value(s) that designates that sample as having a "positive" outcome. A bias measure is a function that returns a bias metric. A bias metric is a numerical value indicating the level of bias detected as determined by a particular bias measure. A collection of bias metrics for a given dataset or a combination of a dataset and model. -
25
FOML is an expressive logic rule language that supports object modeling, analysis, and inference. It naturally supports model-level activities, such as constraints (extending UML diagrams), dynamic compositional modeling, analysis and reasoning about models, model testing, design pattern modeling, specification of Domain Specific Modeling Languages, and meta-modeling. FOML can reason about: 1. The model meta-data (meta-model level reasoning, or syntax reasoning) 2. ...
