The learNN package makes it easy to become familiar with the way neural networks work by demonstrating the key concepts using straightforward code examples. The package is based on previous post on this blog.
Andrew Trask wrote an amazing post at I am Trask called:
In the post Hand Coding a Neural Network I’ve translated the Python code into R.
In a follow up post called:
Andrew shows how to improve the network with optimisation through gradient descent.
The package can now be installed from CRAN using:
After installation, the package can be loaded using:
For information on using the package, please refer to the help files.
For examples of usage, see the function-specific help pages.
An overview of the changes is available in the NEWS file.
A development version can be installed at your own peril, using: