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  • 1
    nGraph

    nGraph

    nGraph has moved to OpenVINO

    ...Additionally, we have integrated nGraph with PlaidML to provide deep learning performance acceleration on Intel, nVidia, & AMD GPUs. nGraph Compiler aims to accelerate developing AI workloads using any deep learning framework and deploying to a variety of hardware targets. We strongly believe in providing freedom, performance, and ease of use to AI developers. Our documentation has extensive information about how to use nGraph Compiler stack to create an nGraph computational graph, integrate custom frameworks, and to interact with supported backends.
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  • 2
    Machine Learning Yearning

    Machine Learning Yearning

    Machine Learning Yearning

    ...The point of this book is not to teach traditional machine learning algorithms, but to teach you how to make machine learning algorithms work. Some technical courses in AI will give you a tool, and this book will teach you how to use those tools. If you aspire to be a technical leader in AI and want to learn how to set a direction for your team, this book will help. This book is still a sample draft. In order to make the corresponding Chinese content available to you as soon as possible, the translation time is rushed, and some of the content is inevitably oversight. ...
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  • 3
    Requests for Research

    Requests for Research

    A living collection of deep learning problems

    ...The project functions as a living document of research directions rather than a codebase, making it an accessible entry point for those looking to contribute to the advancement of AI.
    Downloads: 4 This Week
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  • 4
    Edward

    Edward

    A probabilistic programming language in TensorFlow

    A library for probabilistic modeling, inference, and criticism. Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilistic models, ranging from classical hierarchical models on small data sets to complex deep probabilistic models on large data sets. Edward fuses three fields, Bayesian statistics and machine learning, deep learning, and probabilistic programming. Edward is built on TensorFlow. It...
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    $300 Free Credits for Your Google Cloud Projects

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  • 5
    Swift AI

    Swift AI

    The Swift machine learning library

    Swift AI currently depends on Apple's Accelerate framework for vector/matrix calculations and digital signal processing.
    Downloads: 0 This Week
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  • 6
    Grenade

    Grenade

    Deep Learning in Haskell

    Grenade is a composable, dependently typed, practical, and fast recurrent neural network library for concise and precise specifications of complex networks in Haskell. Because the types are so rich, there's no specific term level code required to construct this network; although it is of course possible and easy to construct and deconstruct the networks and layers explicitly oneself. Networks in Grenade can be thought of as a heterogeneous list of layers, where their type includes not only...
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  • 7
    Caffe

    Caffe

    A fast open framework for deep learning

    ...Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and a great community of contributors that continue to make Caffe state-of-the-art in both code and models. It’s been used in numerous projects, from startup prototypes and academic research projects, to large scale industrial applications.
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  • 8
    ai trading

    ai trading

    The aim is to build a prototype of agent able to trade by himself

    The aim is to build a prototype of agent able to trade by himself selecting his own criterias and strategies based on its AI capability. Deep learning AI autonomous agent to build FX trading strategies
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