Project 2022 - AI and Neural Networks

Created as part of Data Science and Visualization Application.

For example usage see Implementation Examples

Documentation can be found here.

Features

• Classification and Regression using RandomForest or Neural Networks
• Plotting options:
• Classification:
  • Confusion matrices
  • feature importance (random forest only)
  • training history (neural net only)
• Regression
  • Model fit (y_train vs prediction on x_train)
  • Prediction
  • feature importance (random forest only)
  • training history (neural net only)

To install the needed modules:

pip install -r requirements.txt