Mastering data governance For countless organizations, data stands as a priceless treasure. Yet, it’s data governance that serves as the compass guiding one to extract the true worth of data. Envision data governance as a holistic amalgamation of principles, methodologies, and tools designed to oversee the entire life cycle of your data, ensuring it’s in […]
Understanding the path of data Modern organizations grapple with an avalanche of data from diverse origins. Grasping where this data originates, as well as its consumption patterns, is crucial for assuring its quality and reliability. This is where data lineage emerges as a potent instrument, enabling a clearer overview of data within organizations. Essentially, data […]
We can then see the visual interpretation (Figure 14.1) of which tokens impact the final decision the most: # Sample tweet to explaintweet = “I love using the new feature!So helpful.”# Generate the explanationexp = explainer.explain_instance(tweet, predictor, num_features=5, top_labels=3)exp.show_in_notebook() In this case, num_features determines how many features the explainer should use to describe the prediction. […]
Troubleshooting and analysis Regardless of stringent checks, data processes can falter. Here, data lineage shines by assisting teams in pinpointing the origin of errors in their systems, whether in data pipelines, applications, or models. Such pinpoint accuracy drastically trims down the debugging duration, translating to immense time and effort savings. In summary, the systematic mapping […]
Introduction to the COMPAS dataset case study In the realm of machine learning, where data drives decision-making, the line between algorithmic precision and ethical fairness often blurs. The COMPAS dataset, a collection of criminal offenders screened in Broward County, Florida, during 2013-2014, serves as a poignant reminder of this intricate dance. While, on the surface, […]
Understanding the task/outlining success The core of our investigation is binary classification. Our mission can be encapsulated in the question: “Considering various attributes of an individual, can we predict the likelihood of them re-offending, both efficiently and impartially?” The notion of efficiency is straightforward. We have an arsenal of metrics such as accuracy, precision, and […]
Preparing the data for modeling Having understood the nuances of the bias and fairness definitions, it’s crucial that we give the same attention to our data preparation process. This involves not just the technical transformations but also a thoughtful consideration of the implications of these transformations on fairness. Feature engineering We’ve already touched on a […]
