.. title:: User Guide .. _user_guide: User Guide ++++++++++ This part of the documentation contains a user guide to a variety of *Fairness*, *Accountability* and *Transparency* algorithm. As opposed to the rest of the documentation, the user guide is focused on describing the theoretical and implementation (from a functional requirements point of view) aspects of FAT algorithms when applied to the three main components of a data processing pipeline: *data*, *models* and *predictions*. Each entry in the user guide gives the description of the method, intended use of the method, available implementations in a variety of programming languages, best practices, advised usage and caveats, among many other listed properties. .. note:: Additional learning resources are available on the FAT Forensics `events website`_. .. _user_guide_fairness: Fairness User Guide =================== The *Fairness User Guide* discusses techniques used for *detecting*, *measuring* and *mitigating* *bias* and *unfairness* in data and predictive algorithms. .. note:: Coming Soon. .. _user_guide_accountability: Accountability User Guide ========================= The *Accountability User Guide* discusses *safety*, *security*, *robustness* and *privacy* aspects of data sets and predictive algorithms. .. note:: Coming Soon. .. _user_guide_transparency: Transparency User Guide ======================= The *Transparency User Guide* tackles *interpretability* and *explainability* of data sets, predictive models and their predictions. .. toctree:: :maxdepth: 1 :titlesonly: :name: user-guide-transparency transparency/surrogates .. _`events website`: https://events.fat-forensics.org/