Showing 10 open source projects for "artificial neural network code"

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  • 1
    Netron

    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. There is an extense variety of sample model files to download or...
    Downloads: 34 This Week
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  • 2
    Teachable Machine

    Teachable Machine

    Explore how machine learning works, live in the browser

    Teachable Machine is the open-source implementation of an experimental machine learning tool created by Google Creative Lab that allows users to train simple machine learning models directly in a web browser. The project demonstrates how neural networks can be trained interactively using images captured from a webcam or other inputs without requiring programming knowledge. Users can provide example images for different categories, and the system trains a model that learns to classify those...
    Downloads: 9 This Week
    Last Update:
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  • 3
    neurojs

    neurojs

    A JavaScript deep learning and reinforcement learning library

    neurojs is a JavaScript framework designed to enable deep learning and reinforcement learning directly within web environments. The library provides a full machine learning framework implemented in JavaScript that can run inside browsers or Node.js environments. It focuses particularly on reinforcement learning algorithms, enabling developers to create intelligent agents that learn through interaction with simulated environments. The framework supports neural network architectures and...
    Downloads: 0 This Week
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  • 4
    CNN Explainer

    CNN Explainer

    Learning Convolutional Neural Networks with Interactive Visualization

    In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own...
    Downloads: 0 This Week
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    CrypTen

    CrypTen

    A framework for Privacy Preserving Machine Learning

    CrypTen is a research framework developed by Facebook Research for privacy-preserving machine learning built directly on top of PyTorch. It provides a secure and intuitive environment for performing computations on encrypted data using Secure Multiparty Computation (SMPC). Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic...
    Downloads: 0 This Week
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  • 6
    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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  • 7
    NN-SVG

    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. The tool provides the ability to...
    Downloads: 0 This Week
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  • 8
    DeepTraffic

    DeepTraffic

    DeepTraffic is a deep reinforcement learning competition

    DeepTraffic is a deep reinforcement learning simulation designed to teach and evaluate autonomous driving algorithms in a dense highway environment. The system presents a simulated multi-lane highway where an AI-controlled vehicle must navigate traffic while maximizing speed and avoiding collisions. Participants design neural network policies that determine the vehicle’s actions, such as accelerating, decelerating, changing lanes, or maintaining speed. The project was created as part of an...
    Downloads: 0 This Week
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  • 9
    Machine-Learning-Flappy-Bird

    Machine-Learning-Flappy-Bird

    Machine Learning for Flappy Bird using Neural Network

    Machine-Learning-Flappy-Bird is an educational machine learning project that demonstrates how an artificial intelligence agent can learn to play the Flappy Bird game using neural networks and evolutionary algorithms. The system simulates a population of birds that each possess their own neural network, which acts as a decision-making controller during gameplay. The neural network receives input features representing the bird’s position relative to the next obstacle and determines whether the bird should flap or remain idle. ...
    Downloads: 0 This Week
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  • 10
    ConvNetJS

    ConvNetJS

    Deep learning in Javascript to train convolutional neural networks

    ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. ...
    Downloads: 0 This Week
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