Do your models usually get deployed? Or are many of even your best models never actually launched into production?
We want to know:
What Percentage of Your Machine Learning Models Have Been Deployed?
Industry buzz indicates that a high number of machine learning projects fail to reach deployment. That is, many models, including those that are analytically sound, are never integrated into operations. If you or your company’s track record is less than stellar in this regard, you may be shy to proclaim it — but now is the time for honesty (and anonymity). On the other hand, if your models are always or usually deployed, the world will benefit from hearing from you, too.
Please take a moment to participate in this quick KDnuggets’ poll.
You must be logged in to post a comment.
Pingback: What Percentage of Your Machine Learning Models Have Been Deployed? « Machine Learning Times – The Predictive Analytics Times – Nommu
Pingback: What Percentage of Your Machine Learning Models Have Been Deployed? « Machine Learning Times – The Predictive Analytics Times – Init0
Air currents move clouds around the globe, cloud molecules collide with each other, combine, increase in size and fall as precipitation (rain). Precipitation in the form jigsaw puzzle of snow accumulates in mountains of snow and glaciers that can keep water frozen for thousands of years. In warmer climates, when spring arrives, the snow melts and flows over the ground, sometimes forming floods.
Pingback: What Percentage of Your Machine Learning Models Have Been Deployed? « Machine Learning Times – The Predictive Analytics Times - AI Caosuo