Displaying 1 to 20 from 83 results

backbone-react-component - A bit of nifty glue that automatically plugs your Backbone models and collections into your React components, on the browser and server

  •    Javascript

Backbone.React.Component is a mixin and API that glues Backbone models and collections into React components. When used as a mixin the component is mounted, a wrapper starts listening to models and collections changes to automatically set your component state and achieve UI binding through reactive updates.

Awesome-CoreML-Models - Largest list of models for Core ML (for iOS 11+)

  •    HTML

We've put up the largest collection of machine learning models in Core ML format, to help iOS, macOS, tvOS, and watchOS developers experiment with machine learning techniques. We've created a site with better visualization of the models CoreML.Store, and are working on more advance features. If you've converted a Core ML model, feel free to submit an issue.

django - The Web framework for perfectionists with deadlines.

  •    Python

Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Thanks for checking it out.

microstates.js - Composable State Primitives for JavaScript

  •    Javascript

Microstates makes working with pure functions over immutable data feel like working with the classic, mutable models we all know and love. But, most imporantly, Microstates makes working with state fun.




bolt - Bolt Compiler (Firebase Security and Modeling)

  •    TypeScript

Bolt is an experimental security and rules compiler for Firebase Realtime Database (not for Firebase Cloud Storage). It is currently in beta. The language definition is converging, but not yet finalized. We welcome experimentation, but ask that you hand-verify the resulting JSON output before using with production applications. Otherwise, we'd love to have feedback from early adopters. You can email questions to firebase-talk@googlegroups.com using "Bolt" in the subject line, or post bugs on our Issue Tracker.

tf_trt_models - TensorFlow models accelerated with NVIDIA TensorRT

  •    Python

This repository contains scripts and documentation to use TensorFlow image classification and object detection models on NVIDIA Jetson. The models are sourced from the TensorFlow models repository and optimized using TensorRT. Flash your Jetson TX2 with JetPack 3.2 (including TensorRT).

CV-pretrained-model - A collection of computer vision pre-trained models.

  •    

A pre-trained model is a model created by some one else to solve a similar problem. Instead of building a model from scratch to solve a similar problem, we can use the model trained on other problem as a starting point. A pre-trained model may not be 100% accurate in your application. For example, if you want to build a self learning car. You can spend years to build a decent image recognition algorithm from scratch or you can take inception model (a pre-trained model) from Google which was built on ImageNet data to identify images in those pictures.

gradio - Create UIs for prototyping your machine learning model in 3 minutes

  •    Python

Quickly create customizable UI components around your models. Gradio makes it easy for you to "play around" with your model in your browser by dragging-and-dropping in your own images, pasting your own text, recording your own voice, etc. and seeing what the model outputs. You can find an interactive version of this README at https://gradio.app/getting_started.


Pandas - Powerful Python Data Analysis Toolkit

  •    Python

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions. It supports aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets, High performance merging and joining of data sets, Time series-functionality, Hierarchical axis indexing and lot more.

laravel-model-caching - Eloquent model-caching made easy.

  •    PHP

I created this package in response to a client project that had complex, nested forms with many <select>'s that resulted in over 700 database queries on one page. I needed a package that abstracted the caching process out of the model for me, and one that would let me cache custom queries, as well as cache model relationships. This package is an attempt to address those requirements. For best performance a taggable cache provider is recommended (redis, memcached). While this is optional, using a non-taggable cache provider will mean that the entire cache is cleared each time a model is created, saved, updated, or deleted.

plank - A tool for generating immutable model objects

  •    Swift

Plank is a command-line tool for generating robust immutable Objective-C models from JSON Schemas. It will save you time writing boilerplate and eliminate model errors as your application scales in complexity. Models are defined in JSON, a well-defined, extensible and language-independent specification.

mongoose-validator - Validators for mongoose models utilising validator.js

  •    Javascript

Validators for Mongoose schemas utilising validator.js. Mongoose Validator simply returns Mongoose style validation objects that utilises validator.js for the data validation.

mongoose-deep-populate - Mongoose plugin to enable deep population of nested models

  •    Javascript

Mongoose plugin to enable population of nested models at any level of depth. Support Mongoose 3.8.x and later. Refer to changelog for breaking changes. Specify whitelist option to ensure only certain paths can be populated. This is to prevent potential performance and security issues if you allow API clients to supply population paths.

tcomb-validation - Validation library based on type combinators

  •    Javascript

If you don't know how to define types with tcomb you may want to take a look at its README file. Note.

ts-express-decorators - :triangular_ruler: A TypeScript Framework on top of Express

  •    TypeScript

Ts.ED is a framework on top of Express to write your application with TypeScript (or in ES6). It provides a lot of decorators to write your code. Important! TsExpressDecorators requires Node >= 6, Express >= 4, TypeScript >= 2.0 and the experimentalDecorators, emitDecoratorMetadata, types and lib compilation options in your tsconfig.json file.

Silverlight 3D Model Importer

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Silverlight 3D Model Importer allows to work with models processed using Xna Content Pipeline inside a Silverlight 5 (beta) project. It includes all vertex / index buffers data, as well, as textures, bones and mesh / mesh parts info, and provide easy methods to render in SL

models - The ONNX Model Zoo is a collection of pre-trained, state-of-the-art models in the ONNX format

  •    Jupyter

The ONNX Model Zoo is a collection of pre-trained models for state-of-the-art models in deep learning, available in the ONNX format. Accompanying each model are Jupyter notebooks for model training and running inference with the trained model. The notebooks are written in Python and include links to the training dataset as well as references to the original paper that describes the model architecture. The notebooks can be exported and run as python(.py) files. The Open Neural Network eXchange (ONNX) is a open format to represent deep learning models. With ONNX, developers can move models between state-of-the-art tools and choose the combination that is best for them. ONNX is developed and supported by a community of partners.






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