Search Results for "model-builder" - Page 36
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Showing 1820 open source projects for "model-builder"
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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.
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Blendid
Blend of gulp tasks combined into a configurable asset pipeline
Blendid is a delicious stand-alone blend of tasks and build tools poured together as a full-featured modern asset pipeline. It can be used as-is as a static site builder, or can be configured and integrated into your own development environment and site or app structure. The provided command will create default src and config files in your directory and start compiling and live-updating files! Try editing them and watch your browser auto-update! File structure is configured through a config/path-config.json file. ... -
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Util
Java util library with many goodies that will blow Your mind.
My Java util library. It contains many variations of Enumerations, Iterators, Collections, Sets and Maps (e.g. Map2D, Map3D, InvertibleMap, SetMap). It also contains very nice Model-View-Adapter framework. Necessarily see the AnotherClass interface. It will blow your mind. Furthermore it contains interfaces like: Hierarchical, Factory, Converter, Overridable, Persistable, Bindable, Sequential and many other. -
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Freezer Persistence
Freezer: Easy generation of the persistence layer of your application
Freezer is a Java code generator which can easily generate the persistence layer of your Java application, and it can as well expose easily Tables/Views/Procedures/Functions of your database as Microservices, Webservices or RESTful services. The resulting application may be easily deployed as a stand-alone application, as a web application or as a microservice running in Docker/Kubernates which may be consumed from: - A client application consuming the generated Webservices. - An... -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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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doT
The fastest + concise javascript template engine for nodejs
...templating engine ever made, that is particularly useful in all code generation scenarios where manipulating AST is overkill. doT allows arbitrary JavaScript code in templates, making it one of the most flexible and powerful templating engines. It means that doT security model assumes that you only use trusted templates and you don't use any user input as any part of the template, as otherwise it can lead to code injection. -
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Skalli
IVS & ILRS Reference Point Determination
Skalli is a simple tool to estimate the IVS (International VLBI Service for Geodesy and Astrometry) and ILRS (International Laser Ranging Service) reference point of a radio or laser telescope. -
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Ness PHP
A php framework with zero configuration.
Website: https://nessphp.github.io GitHub: https://github.com/nessphp Documentation: https://nessphp.github.io/docs/index.html Donate: https://paypal.me/sinansalichasan Welcome to Ness PHP Framework. Do you need a web framework with minimized training effort? Ness PHP offers you a model-view-controller based environment for coding faster, safer and stronger web applications with (nearly) zero configuration. Get rid of mess and focus the main logic of your project Ness PHP is an excellent but straightforward application development framework which aims to help you in your coding process by speeding up development with ready to use libraries that require minimal configuration. -
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PyTorch Natural Language Processing
Basic Utilities for PyTorch Natural Language Processing (NLP)
...PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out this example code for training on the Stanford Natural Language Inference (SNLI) Corpus. Now you've setup your pipeline, you may want to ensure that some functions run deterministically. Wrap any code that's random, with fork_rng and you'll be good to go. Now that you've computed your vocabulary, you may want to make use of pre-trained word vectors to set your embeddings. -
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Incremental DOM
An in-place DOM diffing library
Incremental DOM is a lightweight library for building DOM trees by issuing imperative update instructions, avoiding heavyweight virtual DOM diffing at runtime. Instead of creating and diffing large object graphs, templates compile to a sequence of function calls that “patch” the live DOM in place. This model eliminates allocations associated with virtual trees and allows updates to be streamed directly to the DOM, which can improve memory usage and reduce GC pressure. It integrates naturally with template compilers (such as those that generate calls from HTML-like markup) but can also be used by hand for fine-tuned rendering. The library is small and focused: it manages element creation, attribute updates, and text nodes while leaving state management and data flow to the host framework. ... -
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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Python Patterns
A collection of design patterns/idioms in Python
Python-Patterns is a repository collecting implementations of many classical design patterns and idioms, written in Python. It serves as an educational resource: showing how to implement creational, structural, behavioral, testability, and other patterns in a Pythonic style (or sometimes less so), illustrating trade-offs, different styles, and use cases. It’s intended for learners or developers interested in software architecture or design, rather than as a production library. Includes... -
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SwiftSVG
A simple, performant, and lightweight SVG parser
SwiftSVG is not meant to be a full SVG parser. The library supports the most common use cases of flat, solid-color SVG elements. It supports grouping and transformations and can parse all path and shape elements. The best use case for SwiftSVG is for flat icons that you may want to theme at runtime and have good control over. Think icons for your app, especially if you offer light and dark themes. The library can handle complex paths, and more importantly can handle them quickly, so you can... -
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Handy Application Maker
Software builder for both veteran programmer and novice.
Software builder for both veteran programmer and novice. -
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setupdocx
Multidocument automation by templates - for sphinx, mkdocs, epydoc ...
...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 commands: - build_docx - Enhanced documentation. - install_docx - Installs local documentation. - dist_docx - Documentation packaging. - build_apidoc - Standalone Generator for API Documentation - build_apiref - Standalone Generator for API Reference -
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Smart Application Maker
Database application creator/builder/maker/producer/designer for user
Database application creator/builder/maker/producer/designer for user with zero programming knowledge. It is the smart version of Handy Application Maker. The objective is to optimize the usability and the user friendliness to produce software. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with both RGB and optical flow input streams. The models have achieved state-of-the-art results on benchmark datasets such as UCF101 and HMDB51, and also won first place in the CVPR 2017 Charades Challenge. ... -
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html5-canvas-2d-grid-layout
A simple grid model system for drawing shapes in an HTML canvas
This project allows the user to define a grid configuration model for a canvas within an HTML document. The grid configuration allows the user to specify height and width of grid "units". Once the grid configuration is defined, the user can create an draw certain shapes and lines, specifying locations in "units" of where objects should be placed in the canvas. Shapes and lines support configuration themselves for color, stroke width, etc. -
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nlp_chinese_corpus
Large Scale Chinese Corpus for NLP
...Each dataset includes descriptions, download links, structure notes, and examples to help users understand how the data is formatted. The corpora can support tasks such as language model pretraining, word vector training, question answering, title generation, keyword generation, translation, and sentence representation learning. Overall, it is a practical resource hub for building or testing Chinese NLP models with larger and more varied datasets. -
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MLBox
MLBox is a powerful Automated Machine Learning python library
...Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. Your help is very valuable to make it better for everyone. -
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React Sortable HOC
Turn any list into an animated, accessible and sortable list
...It provides a set of utilities that allow developers to create sortable interfaces with smooth animations and minimal effort. The library is built on top of React’s component model, making it easy to integrate into existing applications. It supports features such as keyboard accessibility, customizable drag handles, and dynamic list updates. The system is designed to handle both simple and complex sorting scenarios, including nested lists and grid layouts. It also includes performance optimizations to ensure smooth interactions even with large datasets. ... -
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MMF
A modular framework for vision & language multimodal research
...MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. MMF is built on top of PyTorch that brings all of its power in your hands. MMF is not strongly opinionated. So you can use all of your PyTorch knowledge here. MMF is created to be easily extensible and composable. ... -
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X-DeepLearning
An industrial deep learning framework for high-dimension sparse data
...Storage and communication optimization, parameters are automatically allocated globally without manual intervention, and requests are merged to completely eliminate computing/storage/communication hotspots of ps. Complete streaming training features including feature admission, feature elimination, model incremental export, feature counting statistics, etc. Background: XDL1.0 focuses on throughput optimization and adopts the one request per thread processing model, which can significantly improve the limit throughput under ultra-high concurrency. -
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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RobotsDisallowed
A curated list of the most common and most interesting robots.txt
RobotsDisallowed is a public catalog that tracks websites and organizations explicitly blocking AI and web-scraping crawlers in their robots.txt or related mechanisms. It focuses on documenting the growing trend of content owners asserting control over how their data is used for model training and automated harvesting. The project aggregates domains, notes the targeted bots or user agents, and surfaces patterns for researchers, policymakers, and tool builders. It serves both as a transparency effort and as a resource for people designing allow/deny strategies for automated access. The dataset invites community contributions to keep the picture current as new bots emerge and policies shift. ... -
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Dep
Go dependency management tool experiment
...Note that dep requires a functioning Go workspace and GOPATH. Dep is centered around the idea of the "four state system" - a model for classifying and organizing the on-disk state with which a package manager interacts. This was first articulated as a coherent, general model in this (long) article, though many of the principles in the four state model were derived from existing package managers. -
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Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments to solve. ...
