This is an assortment of miscellaneous scripts, programs, and datasets that deal with Artificial Neural Networks (ANN). Over the course of my dissertation work, I assembled the items in this repository to learn, break, and understand how ANNs work and what you can (and cannot) do with them. Some of the code here was used to build solutions and sketches for class assignments.
Most of the scripts in this repository are implementations in Python 3, or R. Some bash scripts are peppered around that serve as driver routines, or test cases, for a specific problem; but for the most part the solution implementations are in either Python or R.
Visualizations are in either MatPlotLib or GGPlot, depending on the main language and task.
- Download the Code and follow the standard instructions on how to install the framework/library.
- If you found a bug, open an issue and please provide detailed steps to reliably reproduce it.
- If you have feature request, open an issue.
- If you would like to contribute, please submit a pull request.
The basic requirements for the software are:
- Python 3, version 3.6.1.
- R, version 3.3.1.
You will need a reasonably modern computer and operating system that can support the above.
Contact Camilo Valdes for pull requests, bug reports, good jokes, and coffee recipes.
The software in this repository is available under the GNU General Public License, version 3. See the LICENSE file for more information.