Digit recognition neural network using the MNIST dataset. Features include a full gui, convolution, pooling, momentum, nesterov momentum, RMSProp, batch normalization, and deep networks.
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Updated
Jun 8, 2020 - C#
Digit recognition neural network using the MNIST dataset. Features include a full gui, convolution, pooling, momentum, nesterov momentum, RMSProp, batch normalization, and deep networks.
It reads handwritten numbers given an input of pixel values. A supervised learning, gradient descent, mini-batching, softmax-output-activation neural network that is meant to be trained on the MNIST dataset (dataset not included in this repository).
Quick test to use font data to create training/testing data and train the model with ML.Net.
A from-scratch basic backpropagation neural network implemented in C#.
Training a Neural network in Unity 3D to recognize handwritten digits from the MNIST dataset
Реализация алгоритма обратного распространения ошибки для обучения нейронной сети для распознавания рукописных цифр
Shows how to create a neural network from scratch in C# without a 3th party library
MNIST Neuronal Network drawing program
MNIST - Handwritten Digit Classification Example
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