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

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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

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

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