Search Results for "mobile learning (lms)"
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Showing 9 open source projects for "mobile learning (lms)"
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ML.NET
Open source and cross-platform machine learning framework for .NET
With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology... -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning... -
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Pion WebRTC
Pure Go implementation of the WebRTC API
Pion implements the WebRTC API. Spend more time building and less time learning a new API. Pion is fast! With quick build times, examples and godoc you will be deploying in no time. Pion works almost everywhere thanks to Go. Ship to Mobile, Desktop, Servers and WASM all with one code base. We built everything from scratch, come learn from our journey. We have docs not just on Pion, but also deep WebRTC knowledge. Pion is owned by the community, no private bugs or roadmaps. Come join... -
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Redwood
The App Framework for Startups
Focus on building your startup, not fighting your framework. Redwood is the full-stack web framework designed to help you grow from side project to startup. Our mission is to help more startups explore more territory, more quickly. We begin by crafting a more integrated framework. We’ve chosen the world’s most popular rendering engine to power Redwood’s web frontend. With React, you’ll have your pick of learning materials, design systems, and trained employees. As your project grows, so... -
Bright Data - All in One Platform for Proxies and Web ScrapingBright Data offers the highest quality proxies with automated session management, IP rotation, and advanced web unlocking technology. Enjoy reliable, fast performance with easy integration, a user-friendly dashboard, and enterprise-grade scaling. Powered by ethically-sourced residential IPs for seamless web scraping.
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
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rax
A progressive React framework for building universal application
Ultra-lightweight, high-performance, easy-to-use front-end solution. One-time development and multi-terminal operation, liberating repetitive work, focusing on product logic, and improving development efficiency. The Rax 1.0 system provides a wealth of components and APIs to help business students quickly develop multi-terminal projects. Go Rax is a Rax 1.0 sample app, which is provided for Rax developers for reference and learning. Rax improves the product experience through a lighter core... -
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FIND3
High-precision indoor positioning framework, version 3
The Framework for Internal Navigation and Discovery (FIND) is like indoor GPS for your house or business, using only a simple smartphone or laptop. Support for any data source, Bluetooth/WiFi/magnetic fields / etc. (previously just WiFi). Passive scanning built-in (previously required a separate server). Support for Bluetooth scanning in scanning utility (previously just WiFi). Meta-learning with 10 different machine learning classifiers (previously just three). Client uses Websockets+React... -
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Accord.NET Framework
Machine learning, computer vision, statistics and computing for .NET
... machine learning, statistics, artificial intelligence, computer vision and image processing methods to .NET. It can be used on Microsoft Windows, Xamarin, Unity3D, Windows Store applications, Linux or mobile. After merging with the AForge.NET project, the framework now offers a unified API for learning/training machine learning models that is both easy to use and extensible. -
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Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind. Caffe2 is a deep learning framework that provides an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2’s cross-platform... -
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