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GitHub - siekmanj/sieknet: A neural network/deep learning library implemented fr...
source link: https://github.com/siekmanj/sieknet
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README.md
sieknet
This is a dependency-free neural network/deep learning library I am attempting to write from scratch in C.
I have used the following resources extensively in the course of this project:
- Michael Nielsen's excellent online book
- 3blue1brown's YouTube series
- Wikipedia's article on Recurrent Neural Networks
- Andrej Karpathy's article on RNN's
- Eli Bendersky's article on the softmax function
So far, I have implemented:
- A feed-forward neural network which you can find under
/networks/MLP/. - A recurrent neural network, which you can find under
/networks/RNN/. - Backpropagation.
- Softmax activation and cross-entropy cost.
Various demonstrations of how to use the networks can be found in /examples/. Currently, I am using Shakespeare's sonnets to train a 512x512x512 recurrent network to compose a sonnet.
To do a quick-and-dirty demo:
git clone https://github.com/siekmanj/sieknet
cd sieknet/build
make recurrent_demo && ./recurrent_demo.out
In the coming months, I intend to implement:
- A LSTM network.
- A convolutional neural network.
- Geoffrey Hinton's Capsule network
- Filip Pieknewski's Predictive Vision Model
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