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Showing 5 open source projects for "network graph analysis"

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  • Atera all-in-one platform IT management software with AI agents Icon
    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.
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    HOA Software

    Smarter Community Management Starts Here

    Simplify HOA management with software that handles everything from financials to communication.
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    easyrec
    easyrec is a recommender system that aims for easy integration of recommendations into web applications. It has a web based admin tool, and its recommendation engine is accessible through a REST API, providing methods like 'other users also bought'
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  • 2

    HadStat

    HadStat is service on cloud,for data analysis using Hadoop MapReduce.

    HadStat is service on the cloud, allow you to analysis the data on the cloud and return the result in nice graph,this service is free, you can redistribute it and/or modify it under the terms of the GNU General Public License. this service using many technologies , like Hadoop mapreduce, HTML, PHP, Web Service applications, linux server, java, eclipse IDE, with many indicators:Simple moving average (SMA),Exponential moving average (EMA),Smoothed simple moving average (SMMA),Linear weighted moving average (LWMA )on DATA from NYSE daily prices.....
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  • 3
    SPIDR Network Access and Analysis Protocol This project provides an advanced web service API to data and analytical tools, comprised of synchronous and asynchronous granule retrieval, multi-part streaming, self-describing documentation, and metadata
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  • 4
    The purpose of eAudit is to provide a comprehensive reporting capability relating to Electronic Auditing for various industries.
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    Create and run cloud-based virtual machines.

    Secure and customizable compute service that lets you create and run virtual machines.

    Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
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  • 5
    EDAS2 is a web-based environmental quality data management and decision support framework
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