Interpretable machine learning applications: Part 5

ofrecido por
Coursera Project Network
En este proyecto guiado, tú:

 Be acquainted with the basics of the Aequitas Tool as a tool to measure and detect bias in the outcome of a machine learning prediction model.

Learn more about a real world case study, i.e., predictions of recidivism (COMPAS dataset), and how the prediction model may have been biased.

Learn a technique, which is largely based on statistical descriptors, for measuring bias and fairness for Machine Learning (ML) prediction models.

Clock1.5 hours
BeginnerPrincipiante
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

You will be able to use the Aequitas Tool as a tool to measure and detect bias in the outcome of a machine learning prediction model. As a use case, we will be working with the dataset about recidivism, i.e., the likelihood for a former imprisoned person to commit another offence within the first two years, since release from prison. The guided project will be making use of the COMPAS dataset, which already includes predicted as well as actual outcomes. Given also that this technique is largely based on statistical descriptors for measuring bias and fairness, it is very independent from specific Machine Learning (ML) prediction models. In this sense, the project will boost your career not only as a Data Scientists or ML developer, but also as a policy and decision maker.

Habilidades que desarrollarás

  • Software Engineering
  • Artificial Intelligence (AI)
  • Data Science

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Setting up the stage

  2. First attempt and stage for detecting bias

  3. Second attempt and stage for detecting bias

  4. Third attempt and stage in detecting bias

  5. Visualisation: Final stage for detecting bias

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Preguntas Frecuentes

Preguntas Frecuentes

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