In this episode of the Data Show, I spoke with Nick Pentreath, principal engineer at IBM. Pentreath was an early and avid user of Apache Spark, and he subsequently became a Spark committer and PMC member. Most recently his focus has been on machine learning, particularly deep learning, and he is part of a group within IBM focused on building open source tools that enable end-to-end machine learning pipelines. We had a great conversation spanning many topics, including: AI Fairness 360 (AIF360), a set of fairness metrics for data sets and machine learning models Adversarial Robustness Toolbox (ART), a Python library for adversarial attacks and defenses. Model Asset eXchange (MAX), a curated and standardized collection of free and open source deep learning models. Tools for model development, governance, and operations, including MLflow, Seldon Core, and Fabric for deep learning Reinforcement learning in the enterprise, and the emergence of relevant open source tools like Ray. Related...