Showing 9 open source projects for "virtual-machine"

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    Gemini 3 and 200+ AI Models on One Platform

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  • 1
    Smile

    Smile

    Statistical machine intelligence and learning engine

    ...Data scientists and developers can speak the same language now! Smile provides hundreds advanced algorithms with clean interface. Scala API also offers high-level operators that make it easy to build machine learning apps. And you can use it interactively from the shell, embedded in Scala. The most complete machine learning engine. Smile covers every aspect of machine learning.
    Downloads: 6 This Week
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  • 2
    ML.NET

    ML.NET

    Open source and cross-platform machine learning framework for .NET

    With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that automates the process of building best performing models for your Machine Learning scenario. ...
    Downloads: 0 This Week
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  • 3
    NVIDIA NeMo

    NVIDIA NeMo

    Toolkit for conversational AI

    NVIDIA NeMo, part of the NVIDIA AI platform, is a toolkit for building new state-of-the-art conversational AI models. NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI...
    Downloads: 4 This Week
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  • 4
    fastText

    fastText

    Library for fast text classification and representation

    ...Such categories can be review scores, spam v.s. non-spam, or the language in which the document was typed. Nowadays, the dominant approach to build such classifiers is machine learning, that is learning classification rules from examples. In order to build such classifiers, we need labeled data, which consists of documents and their corresponding categories (or tags, or labels).
    Downloads: 0 This Week
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  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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  • 5
    TEXT2DATA

    TEXT2DATA

    Text Analytics Platform

    Bring Text Analytics Platform that uses NLP (Natural Language Processing) and Machine Learning to your work environment. Extract essential information from your text documents and let Artificial Intelligence save your time. Get detailed and agile reports on your unstructured data.
    Downloads: 0 This Week
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  • 6
    Intel neon

    Intel neon

    Intel® Nervana™ reference deep learning framework

    neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. The gpu...
    Downloads: 0 This Week
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  • 7
    Python Machine Learning book

    Python Machine Learning book

    The book code repository and info resource

    ...This is not yet just another "this is how scikit-learn works" book. its aim is to explain how Machine Learning works, tell you everything you need to know in terms of best practices and caveats, and then we will learn how to put those concepts into action using NumPy, scikit-learn, Theano and so on. Many parts of this book will provide examples in scikit-learn, the most beautiful and practical machine learning library.
    Downloads: 0 This Week
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  • 8
    Phrasal

    Phrasal

    Statistical phrase-based machine translation system

    ...Our work ranges from basic research in computational linguistics to key applications in human language technology, and covers areas such as sentence understanding, automatic question answering, machine translation, syntactic parsing and tagging, sentiment analysis.
    Downloads: 0 This Week
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  • 9
    Dutch sentiment analysis engine

    Dutch sentiment analysis engine

    Een module om de sentiment van een stuk Nederlandse tekst to bepalen

    This application was developed by Incentro to satisfy requests by clients for a sentiment analyser for the Dutch language. It is currently in it's alpha stage and we expect to have a beta release by November 2012. If you would like to help with the development or testing of this product please contact us at +31[0]15 76 40 750 - of info {at} incentro.com. Deze applicatie is ontwikkeld door Incentro om te voldoen aan klantaanvragen voor een sentimentanalyse module voor de Nederlandse taal....
    Downloads: 0 This Week
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