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NNDotNetTutorial

Some examples in C# for an introductory tutorial on neural network and deep learning for Windows users.

Example 01 - Creating and using vectors and matrices with the MathNet.Numerics package
Example 02 - A single neuron model 
Example 03 - Expanding the single neuron model to make a single layer of neurons
Example 04 - Expanding the single layer model to create a 2-layer stack

Example 05 - (placeholder) Backpropagation
Example 06 - (placeholder) Restricted Boltzmann Machine (RBM)
Example 07 - (placeholder) Stacked RBMs
Example 08 - (placeholder) 1-hot vector representations
Example 09 - (placeholder) Learning with Stacked RBMs
Example 10 - (placeholder) 2-D Convolutional Neural Network (CNN)
Example 11 - (placeholder) CNNs with pooling and dropout
Example 12 - (placeholder) Long Short Term Memory (LSTM) recurrent networks
Example 13 - (placeholder) Learning sequences with LSTM
Example 14 - (placeholder) Reinforcement Learning

Note that these examples are only for illustrative purposes. For any large scale neural computing
you should use an optimized GPU-capable toolkit such as CNTK, Torch, Theano, Caffe, TensorFlow etc 
if possible. 

CNTK        http://www.cntk.ai/
Torch       http://torch.ch/
Theano      http://deeplearning.net/software/theano/index.html
Caffe       http://caffe.berkeleyvision.org/
TensorFlow  https://www.tensorflow.org/

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