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Showing 6 open source projects for "problem a"
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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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Paessler: Easy to Use With Enterprise Power. Free TrialYou shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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PyMC3
Probabilistic programming in Python
...A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets. -
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A multi-notational modeling toolkit that supports the NFR framework, i* Framework, KAOS, Problem Frames, BPMN and UML notations. For more information, please visit the project's Wiki page at https://sourceforge.net/p/re-tools/wiki/Home/.
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FiniteSatUSE is a tool that provides correctness methods for UML class diagrams. It uses the USE System syntax for specification of the class diagrams.
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SchemaDB
abstract layer for mysql database with magic
Handle your db with magic features automatic schema adapting based on your php classses ** PROGECT NOW ON GITHUB ** GOTO: https://github.com/Javanile/SchemaDB -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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EasyCP
The easiest C++ way to deal with constraints !
EasyCP is a modern, user-friendly C++ library that lets you use constraint programming in a very natural way, taking advantage of its expressive power. Just model and let the CSP (Constraint Satisfaction Problem) solver do the job ! -
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Our goal is to develop a full working solver for ATA (with 1 clock) in Python, with MTL to ATA support. The decidability for the emptiness problem was proposed by Lasota and Walukiewicz. The MTL to ATA was proposed by Ouaknine and Worrell.
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