O'Reilly on Data

MARCH 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. If you can’t walk, you’re unlikely to run.

Management 332

Management Machine Learning Experimentation Metrics 332

Domino Data Lab

FEBRUARY 4, 2019

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams. ethics in AI.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. Keep in mind that data science is fundamentally interdisciplinary. Let’s look through some antidotes.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105