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Cloud tools for web scraping and data extraction
Deploy pre-built tools that crawl websites, extract structured data, and feed your applications. Reliable web data without maintaining scrapers.
Automate web data collection with cloud tools that handle anti-bot measures, browser rendering, and data transformation out of the box. Extract content from any website, push to vector databases for RAG workflows, or pipe directly into your apps via API. Schedule runs, set up webhooks, and connect to your existing stack. Free tier available, then scale as you need to.
The aim of this project is to have a current implementation of the experimental VFER protocol (http://vfer.sf.net) within the ns-2 network simulator. The design of VFER can then be tweaked using results from this simulation.
NS2 Linux is dedicated to improve the Network Simulator (NS-2) to match Linux performance. Planned contents include: an NS-2 module that runs Linux congestion control functions, tutorials on how to run NS-2 to match Linux performance, benchmark for TCP.
SNNSraster is a utility for quick ANN analysis of raster GIS maps with the use of Stuttgart Neural Network Simulator trained network files. It was developed to read and write binary raster files.
SNNSraster is a project of the Geography Laboratory of the University of Siena. The code was developed by Giancarlo Macchi Jánica between 2006 and 2007. SNNSraster's fundamental objective is to improve the ability to integrate the use of artificial neural networks in GIS environments.
Atera all-in-one platform IT management software with AI agents
Ideal for internal IT departments or managed service providers (MSPs)
Atera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
A modern and usable interface for the well known neuronal network simulator SNNS. The GUI acts as a client to serveral servers embedding SNNS and supports team work aspects.
WIPsim (Wireless IP Simulator) is a network simulator for all layers of the OSI model. The current version is focussed on dealing with IPv6. The simulator was started to investigate wireless (data) networks and mobility.
GNNS - GNNS Neural Network Simulator, is both a set of libraries and an interface for creating and learning neural networks. It is aimed to support as many network typs and learning algorithms as possible. GNNS is meant to support different platforms.
RooCARDS is a set of C++ classes written for the ROOT analysis framework
which interface ROOT to the Stuttgart Neural Network Simulator (SNNS). This
interface is based on a concept originally developed by Professor Yibin Pan
at the UW-Madison.