Search Results for "support vector machine"
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Showing 7 open source projects for "support vector machine"
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OpenLayers
A high-performance, feature-packed library for all your mapping needs
...Render vector data from GeoJSON, TopoJSON, KML, GML, Mapbox vector tiles, and other formats. Leverages Canvas 2D, WebGL, and all the latest greatness from HTML5. Mobile support out of the box. Build lightweight custom profiles with just the components you need. Style your map controls with straight-forward CSS. Hook into different levels of the API or use 3rd party libraries to customize and extend functionality. -
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Netron
Visualizer for neural network, deep learning, machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, Keras, TensorFlow Lite, Caffe, Darknet, Core ML, MNN, MXNet, ncnn, PaddlePaddle, Caffe2, Barracuda, Tengine, TNN, RKNN, MindSpore Lite, and UFF. Netron has experimental support for TensorFlow, PyTorch, TorchScript, OpenVINO, Torch, Arm NN, BigDL, Chainer, CNTK, Deeplearning4j, MediaPipe, ML.NET, scikit-learn, TensorFlow.js. -
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Earth Engine API
Python and JavaScript bindings for calling the Earth Engine API
The Earth Engine API provides Python and JavaScript client libraries for Google Earth Engine, a planetary-scale geospatial analysis platform. With it, users compose lazy, server-side computations over massive catalogs of satellite imagery and vector datasets without handling raw files locally. The API exposes functional operators for map algebra, reducers, joins, and machine learning that scale transparently on Earth Engine’s backend. Developers authenticate once, work interactively in notebooks or the Code Editor, and export results to Cloud Storage, Drive, or asset collections. ... -
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Leaflet
Open-source JavaScript library for mobile-friendly interactive maps
Leaflet is a leading open source JavaScript library for creating interactive, mobile-friendly maps. Leaflet is light at just about 38 KB, but is already fully equipped with all the mapping features you could need. Leaflet is simple but efficient. It doesn’t try to do everything for everybody, rather it focuses on making the basic things work perfectly. It comes ready with exceptional layering tools, customization features such as pure CSS3 popups and controls, map controls and more right... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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Twemoji
Simple library that provides standard Unicode emoji for all platforms
Twitter’s open source emoji has you covered for all your project's emoji needs. With support for the latest Unicode emoji specification, featuring 3,245 emojis, and all for free. As an open source project, attribution is critical from a legal, practical and motivational perspective in our opinion. The graphics are licensed under the CC-BY 4.0 which has a pretty good guide on best practices for attribution. Although there are two kinds of parsing supported by this utility, we recommend you... -
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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... -
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NN-SVG
Publication-ready NN-architecture schematics
Illustrations of Neural Network architectures are often time-consuming to produce, and machine learning researchers all too often find themselves constructing these diagrams from scratch by hand. NN-SVG is a tool for creating Neural Network (NN) architecture drawings parametrically rather than manually. It also provides the ability to export those drawings to Scalable Vector Graphics (SVG) files, suitable for inclusion in academic papers or web pages.
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