Jarrod Kahn Jarrod Kahn

slugnet

An experimental deep learning library.

Language Python
Website https://slugnet.jarrodkahn.com/
Repository https://github.com/kahnvex/slugnet
Last Update 5 months ago
Open Issue Count 5
# Clone this project with git
$ git clone https://github.com/kahnvex/slugnet.git

Latest Commits

Watch the code fly by...

SHA Author Message
5fc249a9abeb1df41cfb90c0b003a94f61ec87b0 Jarrod Kahn Remove requirements file
7708ded5123a440c9bd573706e00d3fea8f18193 Jarrod Kahn Run make commands through pipenv
2394a49b284660a23e8916ef1f0a692794e6fe8e Jarrod Kahn Update wording in layers section
1ac5fade9409c1b9dbbd7cd388e5df34a347a6a6 Jarrod Kahn Update wording and add Pipfile
6086f0bf516a0ccacd1a1a21959286ed4e1fbcb2 Jarrod Kahn Update mean pooling docs
dfa45d0af9dfde2f231d9737b67ce9a03abefc48 Jarrod Kahn Remove unused dependency from requirements and add missing dep nose
5423078fed8fe43b7d8f96565ae5a95ccbb7e05e Jarrod Kahn Point readme to docs
41fe9d0b7297849edb6d3a8867aec496d17ca8ca Jarrod Kahn Update google verification
36b0c78f13d67a190775d03d0db78fa6c86d5322 Jarrod Kahn Update google info
71b3f42fc6cc58152d3ab2b7c14cb37fef9a5bf1 Jarrod Kahn Add google verification

Open Issues

Switch backend to pytorch

Switching the backend to pytorch will make development much easier and faster, and perhaps more relevant to the applications users will see in the real world.

Add global average pooling documentation

Add global average pooling documentation and explore feasibility of adding a numpy implementation.

Add docs for ResNet DenseNet

Add short docs section to refer readers to more advanced DL architectures such as ResNet and DenseNet, specifically document in writing and visually how residual layers make use of an identity function to create short paths between early layers and later layers in a network.

Add BatchNormalization layer and documentation

Paper: https://arxiv.org/abs/1502.03167 Deep Learning: Page 309

Add RNN layers, documentation, and usage examples

Add documentation for recurrent neural network layers and usage examples.