Search Results for "c-support.vim"
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Showing 6 open source projects for "c-support.vim"
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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.
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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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smartIDS
Lightweight intrusion detection for IoT and embedded devices.
The aim of the project is a lightweight intrusion detection library for embedded devices which supports MSP430 and ARM Cortex based devices. Features include DSP/SIMD support, IoT and embedded protocols, distributed operation, event and history management, tool supported configuration and visualization. There is a Java port that supports less features. -
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YANG (Yet Another Network Generator - Java) enables you to generate social networks given various social rules observed in the real population. Uses: generate realistic networks to be used in individual-centric models, teaching or benchmarking.
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Implementation of "online" erasure codec for Hadoop Distributed File System (HDFS). It contains native C library integrated with Java code base of HDFS.
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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The project contains algorithms for locating the most central groups in complex networks. In particular implementations of various centrality measures and heuristic search algorithms. All functionality is exposed via XML-RPC for easier exploitation.
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Data Mining Platform is a platform for data mining and analysis. It contains many of the new and sophisticated methods such as kernel-based classification, two-way clustering, bayesian networks, pattern recognition for time series analysis and many other
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