Domino Data Lab

APRIL 3, 2019

Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for We find ways to improve machine learning so that it requires orders of magnitude more data, e.g., deep learning with neural networks. Agile Manifesto get published. for DG adoption in the enterprise.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

JULY 22, 2019

and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries. What I’m trying to say is this evolution of system architecture, the hardware driving the software layers, and also, the whole landscape with regard to threats and risks, it changes things.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JULY 9, 2019

In 2001, Bill Cleveland writes this article saying, “You are doing it wrong.” You can sleep at night as a data scientician and you know you’re not building a random number generator, but the people from product, they don’t want to know just that you can predict who’s going to be at risk.

Data Science 112

Data Science Machine Learning Advertising Modeling 112