An exploration into how to use different TF/Keras models. Further info TBD.
- data: houses data to potentially be analyzed
- notebooks: houses notebooks from which to experiment code
- opensourceKernelsExamples: contains example kernels that properly use the tools
- readingMaterials: contains information on ML and tool utilization
- tensorboard: contains saved tensorboard data. Do not commit tensorboard data to repo unless necessary to share. Clean regularly.
- visualizations: contains saved viz data. Do not commit to repo unless necessary to share. Clean regularly.