Showing 6 open source projects for "radial basis function"

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    Bryt Software is ideal for lending professionals who are looking for a feature rich loan management system that is intuitive and easy to use. We are 100% cloud-based, software as a service. We believe in providing our customers with fair and honest pricing. Our monthly fees are based on your number of users and we have a minimal implementation charge.
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    Agentic AI SRE built for Engineering and DevOps teams.

    No More Time Lost to Troubleshooting

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  • 1
    Bayesian machine learning notebooks

    Bayesian machine learning notebooks

    Notebooks about Bayesian methods for machine learning

    Notebooks about Bayesian methods for machine learning.
    Downloads: 5 This Week
    Last Update:
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  • 2
    GPU Machine Learning Library. This library aims to provide machine learning researchers and practitioners with a high performance library by taking advantage of the GPU enormous computational power. The library is developed in C++ and CUDA.
    Downloads: 0 This Week
    Last Update:
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  • 3
    eANN

    eANN

    eANN is an implementation of several kind of neural networks.

    eANN is an implementation of several kind of neural networks written with the intention of providing a (hopefully) easy to use, and easy to modify, OOP source code. It is possible to have several different sized networks running simultaneously, each functioning independently of the others or acting as inputs between them. It also easy to modify the structure so that neurons (or even whole layers) can be created/pruned during simulation allowing dynamic expansion/contraction of the network.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Breeze a multiple class model neural network development system. Network models include multi-threaded Backpropagation and Radial Basis Function Networks, for time series prediction.
    Downloads: 0 This Week
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  • Turn traffic into pipeline and prospects into customers Icon
    Turn traffic into pipeline and prospects into customers

    For account executives and sales engineers looking for a solution to manage their insights and sales data

    Docket is an AI-powered sales enablement platform designed to unify go-to-market (GTM) data through its proprietary Sales Knowledge Lake™ and activate it with intelligent AI agents. The platform helps marketing teams increase pipeline generation by 15% by engaging website visitors in human-like conversations and qualifying leads. For sales teams, Docket improves seller efficiency by 33% by providing instant product knowledge, retrieving collateral, and creating personalized documents. Built for GTM teams, Docket integrates with over 100 tools across the revenue tech stack and offers enterprise-grade security with SOC 2 Type II, GDPR, and ISO 27001 compliance. Customers report improved win rates, shorter sales cycles, and dramatically reduced response times. Docket’s scalable, accurate, and fast AI agents deliver reliable answers with confidence scores, empowering teams to close deals faster.
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  • 5
    General purpose agents using reinforcement learning. Combines radial basis functions, temporal difference learning, planning, uncertainty estimations, and curiosity. Intended to be an out-of-the-box solution for roboticists and game developers.
    Downloads: 0 This Week
    Last Update:
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  • 6
    Neural network library for C++ applications in Windows and Linux. Multi-Layer perceptron, radial-basis function networks and Hopfield networks are supported. You can interface this with Matlab's Neural Network Toolbox using the Matlab Extensions Pack
    Downloads: 0 This Week
    Last Update:
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