Tutorials

Contents:

• Installation
  • Installation via .exe (Windows)
  • Installation via PyPI (Linux/macOS)
• General GUI features
  • Monte Carlo Sampling
  • Formatting Monte Carlo data
  • Loading a model
  • Training a model
  • Plotting histograms
  • The interactive histrogram
  • Assessment of a models predictive perfomrance
  • Assessment of the scaling of a models predictive performance with sample size
  • Sensititivity analysis with SHAP
  • Making model predictions
  • Finding the optimal feature values
  • Making predictions for multiple datapoints at the same time
  • Subsampling a new Monte-Carlo dataset
• Protein A chromatography
  • Load Monte-Carlo dataset
  • Response and feature selection
  • Training and performance evaluation of surrogate models
  • Sensitivity analysis with SHAP
  • Predicting with the surrogate model
  • Process optimization
  • Batch predictions
  • Monte Carlo sampling the surrogate model
  • Histograms
  • Interactive histograms