Showing 10 open source projects for "neural network vb6"

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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.
    Downloads: 100 This Week
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  • 2
    NanoNeuron

    NanoNeuron

    NanoNeuron is 7 simple JavaScript functions

    Nano-Neuron is a didactic project that reduces the idea of a neuron to a handful of tiny JavaScript functions so learners can see “learning” in action without heavy frameworks. It demonstrates how a scalar input can be linearly transformed with a weight and bias, then adjusted via gradient updates to fit a simple mapping such as Celsius-to-Fahrenheit conversion. The code emphasizes readability over performance, inviting you to step through calculations and watch parameters converge. Because...
    Downloads: 0 This Week
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  • 3
    AUTOMATIC1111 Stable Diffusion web UI
    AUTOMATIC1111's stable-diffusion-webui is a powerful, user-friendly web interface built on the Gradio library that allows users to easily interact with Stable Diffusion models for AI-powered image generation. Supporting both text-to-image (txt2img) and image-to-image (img2img) generation, this open-source UI offers a rich feature set including inpainting, outpainting, attention control, and multiple advanced upscaling options. With a flexible installation process across Windows, Linux, and...
    Downloads: 181 This Week
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  • 4
    CrypTen

    CrypTen

    A framework for Privacy Preserving Machine Learning

    ...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 differentiation and neural network operations. Its design mirrors PyTorch’s modular and library-based structure, enabling flexible experimentation, debugging, and model development. The framework supports both encryption and decryption of tensors and operations such as addition and multiplication over encrypted values. Although not yet production-ready, CrypTen focuses on advancing real-world secure ML applications, such as training and inference over private datasets, without exposing sensitive data.
    Downloads: 0 This Week
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  • 5
    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.
    Downloads: 0 This Week
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  • 6
    NN-SVG

    NN-SVG

    Publication-ready NN-architecture schematics

    ...The tool provides the ability to generate figures of three kinds: classic Fully-Connected Neural Network (FCNN) figures, Convolutional Neural Network (CNN) figures of the sort introduced in the LeNet paper, and Deep Neural Network figures following the style introduced in the AlexNet paper. The former two are accomplished using the D3 javascript library and the latter with the javascript library Three.js. NN-SVG provides the ability to style the figure to the user's liking via many size, color, and layout parameters.
    Downloads: 0 This Week
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  • 7
    Synaptic

    Synaptic

    Architecture-free neural network library for node.js and the browser

    Synaptic is a javascript neural network library for node.js and the browser, its generalized algorithm is architecture-free, so you can build and train basically any type of first order or even second order neural network architectures. This library includes a few built-in architectures like multilayer perceptrons, multilayer long-short term memory networks (LSTM), liquid state machines or Hopfield networks, and a trainer capable of training any given network, which includes built-in training tasks/tests like solving an XOR, completing a Distracted Sequence Recall task or an Embedded Reber Grammar test, so you can easily test and compare the performance of different architectures. ...
    Downloads: 0 This Week
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  • 8
    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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  • 9

    Speedy Composer

    Speedy Composer – Artificial Neural Network Melody Composer.

    Thank you for your interest in Speedy Composer. Speedy Composer is an automated application for composing melodies for Speedy Net members. We recently made changes to the source code of Speedy Net, and converted it into the Python language and Django framework. Since Speedy Composer was originally written in PHP, it is not adapted to work with Speedy Net in its current form. So unfortunately we were forced to temporarily close the app Speedy Composer. But don't worry, we kept backups of all...
    Downloads: 0 This Week
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  • 10
    Turn-based strategy game for developers/technical experienced users, based on neural networks, algorithmic programming languages and other techniques.
    Downloads: 0 This Week
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