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A lightweight and educational implementation of an artificial neural network (ANN) in Go. Designed for simplicity and clarity, this project demonstrates core concepts like forward propagation, backpropagation, and gradient descent.
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51
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docs: remove outdated CUDA usage examples and notes from README.md
cdfde66View on GitHubrefactor: enhance Makefile for improved build commands and add test output messages
15125bfView on GitHubrefactor: update Makefile and .gitignore for improved build process and directory management
560cc07View on GitHubrefactor: update test commands in Makefile to use specific test directories
282dec7View on GitHubrefactor: remove sigmoid functions from neural package and implement in matrix package with CUDA support
4233728View on GitHubincrease training epochs in neural network test for enhanced learning capacity
e22abe4View on GitHubadjust learning rate and training epochs for improved neural network performance
6f6f5d5View on GitHubclarify comment in matrix randomization kernel to specify output range
ac26d95View on GitHubupdate neural network parameters and randomization range for improved training
084a7beView on GitHubadd CUDA support for scalar multiplication and implement corresponding tests
01320e4View on GitHub