Search Results for "community detection algorithm"
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Showing 3 open source projects for "community detection algorithm"
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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shadowsocks-libev
Bug-fix-only libev port of shadowsocks
Shadowsocks-libev is a lightweight secured SOCKS5 proxy for embedded devices and low-end boxes. Shadowsocks-libev is written in pure C and depends on libev. It's designed to be a lightweight implementation of shadowsocks protocol, in order to keep the resource usage as low as possible. Snap is the recommended way to install the latest binaries. You can build shadowsocks-libev and all its dependencies by script. The latest shadowsocks-libev has provided a redir mode. You can configure your... -
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Front end Interview Questions
Help the front End community to rock interview
Interview questions for front-end developers. Only for JS developers when they have to answer some side questions to make the interviewer comfortable. To rock the interview to achieve what you deserve and to improve your concepts about front-end technologies, I have consolidated a list of questions and answers. It's a one-stop solution for front end interview process. HTML might be the heart of a website, but least utilized and explored. js dude followed the same path and put some basic... -
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EMET is an image metadata extraction tool intended to facilitate the management and preservation of digital images and their incorporation into external databases and applications. EMET was created by ARTstor through funding from NDIIPP.
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