Showing 4 open source projects for "machine learning projects"

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  • 1
    Wicked Engine

    Wicked Engine

    3D engine with modern graphics

    Wicked Engine is an open-source 3D engine with modern graphics. Use this as a C++ framework for your graphics projects, a standalone 3D editor, LUA scripting or just for learning. To build Wicked Engine for Windows (10 or later), use the latest version of Visual Studio and the provided WickedEngine.sln solution file. By simply pressing F5, the Editor application will be built. There are other example projects that you can build as well within the solution.
    Downloads: 8 This Week
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  • 2
    pyntcloud

    pyntcloud

    pyntcloud is a Python library for working with 3D point clouds

    This page will introduce the general concept of point clouds and illustrate the capabilities of pyntcloud as a point cloud processing tool. Point clouds are one of the most relevant entities for representing three dimensional data these days, along with polygonal meshes (which are just a special case of point clouds with connectivity graph attached). In its simplest form, a point cloud is a set of points in a cartesian coordinate system. Accurate 3D point clouds can nowadays be (easily and...
    Downloads: 0 This Week
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  • 3
    TenorSpace.js

    TenorSpace.js

    Neural network 3D visualization framework

    TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization...
    Downloads: 0 This Week
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  • 4
    Keras.js

    Keras.js

    Run Keras models in the browser, with GPU support using WebGL

    Run Keras models in the browser, with GPU support provided by WebGL 2. Models can be run in Node.js as well, but only in CPU mode. Because Keras abstracts away a number of frameworks as backends, the models can be trained in any backend, including TensorFlow, CNTK, etc. Check out the demos/ directory for real examples running Keras.js in VueJS. Library version compatibility, Keras 2.1.2.
    Downloads: 0 This Week
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