Machine Learning Times
EXCLUSIVE HIGHLIGHTS
Jev Fever: Predictive AI Is Superhot Again
  Originally published in Forbes The more AI changes, the...
GenAI Owns the Hype, but Predictive AI Is Thriving
  EDITOR’S NOTE: This article is adapted from the...
The Data Disconnect: A Key Challenge for Machine Learning Deployment
  EDITOR’S NOTE: This article is excerpted from The...
A Brief History of Why Machine Learning Projects Stall
  EDITOR’S NOTE: This is the preface to The...
SHARE THIS:
  • Nov 7, 2014
  • Comments Off on Want to Improve Your Prototype-to-Production Analytics Process? Embrace Thinking Inside the Box
  • Original Content
  • 6763 Views

12 years ago
Want to Improve Your Prototype-to-Production Analytics Process? Embrace Thinking Inside the Box

 Anyone in the business of analytics knows that the work is often highly iterative, exploratory and ill-defined. In my experience, as hard as it is to fit models that let us understand complex relationships and make predictions, it is often harder still to get such models into production environments. By “production environments” I mean settings where analytics are embedded in a business’s processes, as opposed to living only as pretty graphs in a PowerPoint. The business of analytics also means getting to play with new math and software tools when tackling new problems. I like to do pre-mortems

This content is restricted to site members. If you are an existing user, please log in on the right (desktop) or below (mobile). If not, register today and gain free access to original content and industry news. See the details here.

Comments are closed.