ClearNet

C + Learn + Net

A framework for the creation and training of vanilla and convolutional neural nets only depending on a C compiler and standard library.

Check out some of the examples in the examples directory.

Some Features

• Creation and training of vanilla and convolutional models
• Autodifferentiation engine
• Stochastic gradient descent and other optimization methods
• Saving and loading a model to a file

Examples

All of these functions are used in files in the examples directory.

• xor: Vanilla net creation and training on xor
• lin reg: Vanilla net creation and training on simple linear regression example
• iris: Vanilla net creation and training with stochastic gradient descent on the iris dataset
• full adder: Vanilla net creation and training with momentum on full adder operation
• mnist vanilla: Vanilla net creation and training with momentum and stochastic gradient descent on mnist dataset
• mnist mix: Creation and training of a convolutional net with dense, convolutional and pooling layers using momentum and stochastic gradient descent on the mnist dataset
• mnist convolutional: Creation and training of a convolutional net with convolutional and pooling layers using momentum and stochastic gradient descent on the mnist dataset