Training a Neural network in Unity 3D to recognize handwritten digits from the MNIST dataset
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Updated
May 12, 2019 - C#
Training a Neural network in Unity 3D to recognize handwritten digits from the MNIST dataset
Shows how to create a neural network from scratch in C# without a 3th party library
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).
Digit recognition neural network using the MNIST dataset. Features include a full gui, convolution, pooling, momentum, nesterov momentum, RMSProp, batch normalization, and deep networks.
Реализация алгоритма обратного распространения ошибки для обучения нейронной сети для распознавания рукописных цифр
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#.
MNIST - Handwritten Digit Classification Example
MNIST Neuronal Network drawing program
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