Search Results for "programming learning system"
Sort By:
Showing 82 open source projects for "programming learning system"
View related business solutions-
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.
-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
1
RuView
Turn WiFi signals into real-time human sensing and spatial awareness.
...The system runs on low-cost hardware such as ESP32 sensor meshes and performs signal processing and machine learning directly at the edge. By learning the RF signature of each environment over time, RuView adapts automatically to different spaces and improves its sensing accuracy. Designed for applications ranging from healthcare monitoring to disaster response, it enables spaces to gain spatial awareness using the radio signals already present in the environment. -
2
RustScan
The Modern Port Scanner
The Modern Port Scanner. Find ports quickly (3 seconds at its fastest). Run scripts through our scripting engine (Python, Lua, Shell supported). Scans all 65k ports in 3 seconds. Full scripting engine support. Automatically pipe results into Nmap, or use our scripts (or write your own) to do whatever you want. Adaptive learning. RustScan improves the more you use it. No bloated machine learning here, just basic maths. The usuals you would expect. IPv6, CIDR, file input and more.... -
3
WiFi DensePose
Turn WiFi signals into real-time human pose estimation and detection
WiFi DensePose is a production-oriented implementation of a WiFi-based human pose estimation system that enables real-time full-body tracking using wireless signals rather than cameras. The project demonstrates how commodity mesh routers and signal processing techniques can be leveraged to infer dense human pose information, even through obstacles such as walls. It is designed to showcase the emerging field of RF-based sensing, where machine learning models interpret wireless channel data to reconstruct human movement and posture. ... -
4
PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
Demo Series - Small Business Backup By VeeamWatch this on-demand demo series and learn how to protect your Microsoft 365 data with clear, simple, actionable steps that are easy to implement for businesses of all sizes.
-
5
Nox
Rust implementation of the Fluence network peer
Nox is a decentralized, serverless execution platform for running secure WebAssembly (Wasm) modules over the Fluence peer-to-peer network. It enables developers to build and deploy composable services without central servers, ensuring tamper-resistant logic and trustless computation. Nox is designed to support multi-peer coordination, decentralized app logic, and data privacy, using Fluence’s Aqua programming model. Ideal for Web3 developers, Nox provides the building blocks to run... -
6
Nvitop
An interactive NVIDIA-GPU process viewer and beyond
nvitop is an interactive NVIDIA device and process monitoring tool. It has a colorful and informative interface that continuously updates the status of the devices and processes. As a resource monitor, it includes many features and options, such as tree-view, environment variable viewing, process filtering, process metrics monitoring, etc. Beyond that, the package also ships a CUDA device selection tool nvisel for deep learning researchers. It also provides handy APIs that allow developers... -
7
Sogou C++ Workflow
C++ parallel computing and asynchronous networking engine
As Sogou`s C++ server engine, Sogou C++ Workflow supports almost all back-end C++ online services of Sogou, including all search services, cloud input method, online advertisements, etc., handling more than 10 billion requests every day. This is an enterprise-level programming engine in light and elegant design which can satisfy most C++ back-end development requirements. -
8
Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior... -
9
Beast
HTTP and WebSocket built on Boost.Asio in C++11
Beast is a header-only C++ library that provides low-level HTTP, WebSocket, and networking protocol building blocks on top of Boost.Asio. It is designed for developers who need to build interoperable clients, servers, proxies, gateways, or custom protocol components rather than using a high-level web framework. Beast follows Boost.Asio’s asynchronous model, so it fits naturally into event-driven C++ networking applications. Its algorithms are role-agnostic, meaning the same core abstractions... -
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.
-
10
Spring Cloud Netflix
Integration with Netflix OSS components
This project provides Netflix OSS integrations for Spring Boot apps through autoconfiguration and binding to the Spring Environment and other Spring programming model idioms. With a few simple annotations you can quickly enable and configure the common patterns inside your application and build large distributed systems with battle-tested Netflix components. The patterns provided include Service Discovery (Eureka), Circuit Breaker (Hystrix), Intelligent Routing (Zuul) and Client Side Load... -
11
manticoresearch
Easy to use open source fast database for search
Manticore Search is an easy to use open source fast database for search. Modern MPP architecture and smart query parallelization capabilities allow to fully utilize all your CPU cores to lower response time as much as possible, when needed. Powerful and fast full-text searching which works fine for small and big datasets. Columnar storage support via the Manticore Columnar Library for bigger datasets (much bigger than can fit in RAM). SQL-first: Manticore's native syntax is SQL. It speaks... -
12
Astrape
Optical-packet node transceiver frequency allocation
In an optical network scenario which consists of multiple nodes (whiteboxes) at its edges and ROADMs in-between, the coherent transceiver average laser configuration time is improved. The process is evaluated according to a testbed setup. This is facilitated in the appropriate lab equipment (or via simulation when required). For that purpose, a software agent (Netconf server) residing at the whiteboxes, is developed receiving input from the Software-Defined Networking (SDN) packet... -
13
CLIP-as-service
Embed images and sentences into fixed-length vectors
CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a microservice into neural search solutions. Serve CLIP models with TensorRT, ONNX runtime and PyTorch w/o JIT with 800QPS[*]. Non-blocking duplex streaming on requests and responses, designed for large data and long-running tasks. Horizontally scale up and down multiple CLIP models on single GPU, with automatic load balancing. Easy-to-use. No learning curve, minimalist... -
14
Spektral
Graph Neural Networks with Keras and Tensorflow 2
Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs. Spektral implements some of the most popular layers for... -
15
Tendermint
Tendermint Core (BFT Consensus) in Go
Tendermint Core is a Byzantine Fault Tolerant (BFT) middleware that takes a state transition machine, written in any programming language, and securely replicates it on many machines. Building the most powerful tools for distributed networks. We are Tendermint, a core contributor to the Cosmos Network. Powerful & secure software for the decentralized future. Tendermint has been in the production of private and public environments, most notably the blockchains of the Cosmos Network. we... -
16
Zenoss Community Edition
Zenoss - Intelligent IT Operations Management
Zenoss provides software-defined IT operations for the world’s largest organizations. We deliver the ultimate level of IT service health with simplicity by providing the most granular and intelligent IT service modeling possible, at any scale, and sharing these unique insights with other IT operations management (ITOM) tools to make them more efficient. Zenoss Community Edition is not a “demo” or trial version of Zenoss Enterprise or Zenoss Cloud! Before You install Zenoss Community... -
17
ESP8266 Deauther Version 2
Affordable WiFi hacking platform for testing and learning
Scan for WiFi devices, block selected connections, create dozens of networks and confuse WiFi scanners! Version 3 is in development. It is stable to use, but it is very different. It is command-line based, which allows it to offer not just more features, but make them more customizable. This software allows you to easily perform a variety of actions to test 802.11 wireless networks by using an inexpensive ESP8266 WiFi SoC (System On A Chip). The main feature, the deauthentication attack, is... -
18
xdp
Package xdp allows one to use XDP sockets
Package github /asavie/xdp allows one to use XDP sockets from the Go programming language. With the default UDP payload size of 1400 bytes, running on Linux kernel 5.1.20, on a tg3 (so no native XDP support) gigabit NIC, sendudp does around 980 Mb/s, so practically line rate. TL;DR: in the same environment, sending a pre-generated DNS query using an ordinary UDP socket yield around 30 MiB/s whereas sending it using the senddnsqueries example program yields around 77 MiB/s. Connecting a PC... -
19
Keras TCN
Keras Temporal Convolutional Network
TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the... -
20
LaPath
Learning Automata algorithm for the shortest path problem.
The shortest path problem is solved by many methods. Heuristics offer lower complexity in expense of accuracy. There are many use cases where the lower accuracy is acceptable in return of lower consumption of computing resources. Learning Automata (LA) are adaptive mechanisms requiring feedback from the executing environment to converge to certain states. In the context of network routing, LA residing at intermediate nodes along a path, exploit feedback from the destination node for... -
21
Age and Gender Estimation
Keras implementation of a CNN network for age and gender estimation
Keras implementation of a CNN network for age and gender estimation. This is a Keras implementation of a CNN for estimating age and gender from a face image [1, 2]. In training, the IMDB-WIKI dataset is used. Because the face images in the UTKFace dataset is tightly cropped (there is no margin around the face region), faces should also be cropped in demo.py if weights trained by the UTKFace dataset is used. Please set the margin argument to 0 for tight cropping. You can evaluate a trained... -
22
FastoCloud PRO
IPTV/NVR/CCTV/Video cloud https://fastocloud.com
IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch ... -
23
IPCalc v1.2
This project is an IP calculator to educational usage
A desktop application which is written in Java programming language. You can use it to educational purposes. This application by knowing the host IP address and the subnet mask can count network IP address, broadcast address and how many hosts can be at the network, Also shows binary operations. -
24
Madara
Middleware for distributed applications
...MADARA is composed of several tools and middleware, and the main entry point into the system is the Knowledge and Reasoning Language (KaRL) Engine, which provides a real-time scripting language for nanosecond execution times hooked into a flexible transport layer for distributed reasoning. The KaRL engine also supports object-oriented C++, Java, and Python programming through Containers, classes that provide abstractions and references for variable location within the KaRL Knowledge Base. ... -
25
Deep Learning with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow. To date tensorflow comes in two different packages, namely tensorflow and tensorflow-gpu, whether you want to install the framework with CPU-only or GPU support, respectively. NVIDIA Drivers and CuDNN must be installed and configured before hand. Please refer to the official Tensorflow documentation for further details. Since version 0.9 Theano introduced the libgpuarray in the stable release (it was previously only available in...
