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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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