notebooks

Diffprivlib notebooks

You can also view the notebooks on nbviewer. The notebooks here are broadly listed in order of increasing complexity and difficulty.

1. 30seconds.ipynb: Introducing diffprivlib by training a machine learning model with differential privacy.
2. naive_bayes.ipynb: Training a Naive Bayes classifier using the UCI adult dataset.
3. logistic_regression.ipynb: Training a logistic regression classifier on the UCI adult dataset.
4. linear_regression.ipynb: Training a linear regressor using the UCI diabetes dataset.
5. histograms.ipynb: Using the histogram function to plot distributions of data.
6. accountant.ipynb: Introducing the BudgetAccountant class to track privacy budget spend across multiple operations.
7. pipeline.ipynb: Using an sklearn pipeline to train a differentially private model.
8. exploration.ipynb: Example data exploration workflow using diffprivlib.