Start with the static-tensor-usage example to learn basic tensor operations.
Basic usage examples:
- backprop-regression - linear regression implemented as a 0-layer neural network using backprop
- static-tensor-usage - basic usage of statically typed tensors
- xor - fitting an xor function.
Other examples:
- autoencoder - a simple autoencoder fit with backprop
- gaussian-process - gaussian process example
- gradient-descent - simple gradient descent example without backprop abstractions
- lenet-cifar10 - lenet NN on cifar10 data, using backprop typeclasses
- multivariate-normal - example of random sampling from a multivariate gaussian distribution.
The experimental directory contains work-in-progress experiments/examples.