a simple neural network implementation from a perspective of linear algebra.
the library is mostly developed for recreational and educational purposes for myself
and only depends on the rand-crate for randomization of newly created weight-
and bias matrices.
for a usage example see src/bin/xor.rs, which simulates an XOR-logic-gate using
a small neural network.
currently available features of the library:
- ReLU and Sigmoid activation functions
- the MSE loss function
- a single, down-to-earth struct that contains the whole network
what might happen down the road:
- BCE loss function (requires output layer sigmoid activation - not a trivial addition)
- serde (de-)serialization to easily store checkpoints/training progress.
- perhaps a MNIST example (?)