Interoperability testing for hyperparameter tuning: MLflow, LightGBM, sklearn, and dask-ml
MLflow autologging allows monitoring LightGBM training loss during model training. This behavior is not always expected when we use scikit-learn and dask to tune LightGBM models. This notebook describes how the unexpected behavior manifests and explains some gotchas when using these tools together.
Police shooting in Texas 2016-2019
Jupyter Notebook on police shooting analysis in Texas from 2016 to 2019 (done in collaboration with Texas Justice Initiative)
FAccT 2021. Journalism, data leverage, education, and language models
Summary of Day 3 at FAccT 2021. Julian Anguin’s Markup, language models, measurements, and data average
FAccT 2021. Automated decision-making, causal accountability, and robustness
Summary of Day 2 at FAccT 2021. Automated decision-making, accountability and recourse, and model robustness
FAccT 2021. AI audit, governance, and trustworthiness
Summary of Day 1 at FAccT 2021. Algorithm audit, impact assessment, data governance, trust in AI, and explainable AI
Tutorials at FAccT 2021
FAccT 2021 (virtual) tutorial summary. Causal analysis, XAI, and algorithmic impact
