Machine Learning Models
Originally published in KDnuggets. The latest KDnuggets poll reconfirms today’s dire industry buzz: Very few machine learning models actually get deployed. In this article, I’ll summarize the poll results and argue that this pervasive failure of ML projects comes from a lack of prudent leadership. I’ll also argue that MLops is not the fundamental
Why pretrained machine learning models are often unusable and irreproducible — and what we can do about it. Introduction A useful approach to designing software is through contracts. For every function in your codebase, you start by writing...
By: Sam Koslowsky, Senior Analytic Consultant,
Harte Hanks
You have been invited to serve as a juror in a criminal related case. After hearing testimony, the presiding judge offers a summary of the proceeding. “Evaluate the evidence,” he declares. Whether it was an eyewitness account,...
Some History Machine Learning Models, which have historically been referred to as predictive models, are not new. Any early practitioner in this field would emphasize that the two key deliverables of any model are as follows: its...
