Search Results for "cuda machine learning"
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Showing 11 open source projects for "cuda machine learning"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
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Logan
Logan is a lightweight case logging system based on mobile platform
...To put it simply, the traditional idea is to piece together the problems that appear in the logs of each system, but the new idea is to aggregate and analyze all the logs generated by the user to find the scenes with problems. In the future, we will provide a data platform based on Logan big data, including advanced functions such as machine learning, troubleshooting log solution, and big data feature analysis. -
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++... -
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Uranie
Uranie is CEA's uncertainty analysis platform, based on ROOT
Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is... -
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Greenplum Database
Massive parallel data platform for analytics, machine learning and AI
Rapidly create and deploy models for complex applications in cybersecurity, predictive maintenance, risk management, fraud detection, and many other areas. With its unique cost-based query optimizer designed for large-scale data workloads, Greenplum scales interactive and batch-mode analytics to large datasets in the petabytes without degrading query performance and throughput. Based on PostgreSQL, Greenplum provides you with more control over the software you deploy, reducing vendor... -
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Faum
Fast Autonomous Unsupervised Multidimiensional Classification
This is the proof-of-concept implementation of the FAUM Clustering method. This implementation was used to perform the published results and is now released in the hope that it will be useful. -
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Random Bits Forest
RBF: a Strong Classifier/Regressor for Big Data
We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data... -
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PetaVision
Accelerated Open-Source Neuromorphic Computing
///////// NOTICE We have migrated to GitHub: https://petavision.github.io To clone an updated repository of the PetaVision codebase, please go to our page on GitHub. ///////// PetaVision is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. PetaVision is intended for computational neuroscientists who seek to apply neuromorphic models to hard signal processing problems; both to improve on the... -
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bnns
Research tool for interactive training of artificial neural networks.
BNNS is a research tool for interactive training of artificial neural networks based on the Response Function Plots visualization method. It enables users to simulate, visualize and interact in the learning process of a Multi-Layer Perceptron on tasks which have a 2D character. Tasks like the famous two-spirals task or classification of satellite image data. -
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A High-Order Multi-Variate Approximation Scheme for Arbitrary Data Sets, C implementation of the method described in http://web.mit.edu/qiqi/www/paper/interpolation.pdf, with Python and Fortran interfaces.
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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With miao3d you can train a specific Gaussian Markov Random Field (GMRF) that then can be used to estimate a depthmap ("3D"), given an image ("2D"). A GUI allows inspection of the image + depthmap.
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CompLearn is a general-purpose compression-based machine learning system that uses data compression to learn or data mine patterns in arbitrary data.
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