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    Trending Toward Concept Building - A Review of Model Interpretability for Deep Neural Networks

    We are at an interesting time in our industry when it comes to validating models - a crossroads of sorts when you think about it. There is an opportunity for practitioners...

    Themes and Conferences per Pacoid, Episode 13

    Paco Nathan's latest article covers data practices from the National Oceanic and Atmospheric Administration (NOAA) Environment Data Management (EDM)...

    Product Management for AI

    Pete Skomoroch presented “Product Management for AI” at Rev. This post provides a distilled summary, video, and full transcript. Session Summary Pete...

    Themes and Conferences per Pacoid, Episode 9

    Paco Nathan's latest article features several emerging threads adjacent to model interpretability. Introduction Welcome back to our monthly burst of...

    Themes and Conferences per Pacoid, Episode 7

    Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Introduction Welcome back...

    Themes and Conferences per Pacoid, Episode 3

    Paco Nathan‘s column covers themes that include open source, "intelligence is a team sport", and "implications of massive latent hardware". ...

    Themes and Conferences per Pacoid, Episode 2

    Paco Nathan's column covers themes of data science for accountability, reinforcement learning challenges assumptions, as well as surprises within AI...

    Avoiding a Data Science Hype Bubble

    In this post, Josh Poduska, Chief Data Scientist at Domino Data Lab, advocates for a common taxonomy of terms within the data science industry. The...