The siren song of Hadoop
Hadoop provides power and versatility for data scientists, at the cost of complexity.
With deep learning, the data-rich get richer
Why AIaaS will dominate business applications for deep learning.
From presentation to conversation: How A.I. will transform enterprise apps
Apps will soon shift from dumb repositories to deft assistants.
Job inequality and artificial intelligence in the enterprise
The future has fewer jobs, but those that remain will be better.
Machine learning: The deplorable state of deployment
A failed standard, complex alternatives -- and a way forward.
Machine learning: Clustering and classification on the campaign trail
Discovering and targeting micropopulations for politics and profit
Putting deep learning to work
Hype aside, deep learning can open up new sources of data for business analysis.
Machine learning: Demystifying linear regression and feature selection
The time-tested technique for predicting numbers, and the role of domain knowledge in machine learning.
The cost of an error: Balancing the role of humans and machines
When the cost of an error isn’t trivial, we need better approaches to error mitigation to operationalize and scale machine learning.
Your business should demand more from machine learning
As a businessperson, the ability to make specific, actionable requests of your data scientists, hold them to a high standard and connect their work to relevant action is basic contemporary corporate literacy.
