Showing 5 open source projects for "programming learning system"

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  • 1
    Megatron-LM

    Megatron-LM

    Ongoing research training transformer models at scale

    ...Megatron-LM is widely used in research and industry for pretraining GPT-, BERT-, T5-, and multimodal-style models, with tooling for checkpoint conversion and interoperability with Hugging Face. Overall, it is a production-grade system for organizations pushing the limits of large-scale language model training.
    Downloads: 2 This Week
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  • 2
    Fuzzy machine learning framework

    Fuzzy machine learning framework

    A library and a GUI front-end for fuzzy machine learning

    Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent...
    Downloads: 30 This Week
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  • 3
    moebinv

    moebinv

    C++ libraries for manipulations in non-Euclidean geometry

    ...The source is written in literate programming NoWeb.
    Downloads: 17 This Week
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  • 4
    Bat2015

    Bat2015

    Bachelor of Science (Informatik)

    The toolkit glpk supports methods for mixed integer linear programming (MILP). These methods solve Capital Budgeting Problems (CBP). Unfortunately, glpk does not support any multithreading and there is no feature to distribute problems via network connections. Today, this is a pitiable sight, because modern computer systems are coupled by networks and support multi threading. We create a distributed system with Apache thrift and the C-API of glpk.
    Downloads: 1 This Week
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  • 5
    DBNL

    DBNL

    Dynamic Bayesian Network Library

    DBNL is a cross-platform library that offers a variety of implementations of Bayesian networks and machine learning algorithms. It is a flexible library that covers all aspects of Bayesian netwoks from representation to reasoning and learning. It allows you to create simple static networks as well as complex temporal models with changing structure. It can handle highly non-linear dependencies between multivariate random variables. The particle based inference can answer arbitrary questions given the provided evidence and can even cope with multimodal densities. ...
    Downloads: 0 This Week
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