Deep learning in Rust! This is my first shot at this. It's mostly just a proof of concept right now. The API will change.

We have these models implemented (check out the examples folder):

• MNIST handwritten digit recognition
• char-rnn using LSTM

So far, we have the following layers implemented:

• Matrix multiply (fully connected)
• Add (for bias, for example)
• LSTM
• Softmax
• MSE loss
• Cross entropy loss

We have the following optimizers:

• SGD
• RMSProp

• More layer types (in the order that I'll probably get to them)
  • Conv2d
  • Pooling
  • Dropout
• Allow datatypes other than f32 and implement casting between arrays of primitive numeric types.
• Provide utilities for working with data
  • images
  • tsv and csv
  • raw text data and word embeddings

We have a looong way to go :)

• Fast
• Easy to use
• Portable
• More control when you need it
• Easy to define custom layers
• Readable internal codebase

MIT