Search Results for "python ai ide"
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Showing 6 open source projects for "python ai ide"
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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.
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$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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FRODO 2
Open-Source Framework for Distributed Constraint Optimization (DCOP)
FRODO is a Java platform to solve Distributed Constraint Satisfaction Problems (DisCSPs) and Optimization Problems (DCOPs). It provides implementations for a variety of algorithms, including DPOP (and its variants), ADOPT, SynchBB, DSA... -
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Spyse is a software framework for building multi-agent systems. It allows Python developers to build distributed intelligent systems of multiple cooperative agents based on FIPA, OWL, SOA and many others. Spyse is designed for ease-of-use and fun.
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ActiveGrid is an Enterprise Web 2.0 solution that allows the composition of code-free applications that comply with corporate IT standards. Technologies include Python, Java, XForm, Xpath, WSDL, CSS, XML Schema (XSD), XACML, and BPEL.
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Multi Agent based distributed application. The code can be processed over multiple common machines with fault-tolerance. It is designed to distributively run any Python's script, which can be applied to a given input data set.
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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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Zeus Grid is a Grid Computing environment usefull to run systems in heterogenous machines at same time. In this first step, it will only compile, run and collect application results and file storage.
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