A repository to show the most basic Neural Network implementation possible with different functionality/optimizations.
| Complexity | Features |
|---|---|
| Level 0 | ~100 line basic building blocks of a neural network demonstration in level0.go. Training the neural network is possible with logic in level0training.go. One does not need to train a neural network to use it, which is why these files are split for the most basic level. Based on the first part of Sebastian Lague's video. |
| Level 1 | Planned... |
| Optimized | An advanced implementation of a NN with backpropagated gradient descent using a velocity-momentum model. Runs much faster than Level 0. Based on Sebastian Lague's final neural network implementation from the final section of his video. Still contains bugs. |
Mnist database package available for import under mnist.
.
go get github.com/soypat/neurus/mnist@latest