Machine Learning Times
Machine Learning Times
Watch 3 Videos from Coursera’s New “Machine Learning for Everyone”
  I’m pleased to announce that, after a successful...
97 Things About Ethics Everyone In Data Science Should Know
 Every now and then an opportunity comes along that...
Machine Learning is Transforming Modern Healthcare
 The pandemic has propelled the adoption of innovation and...
It’s a Bird, It’s a Plane, It’s a Classified Flying Object
 How Computer Vision Is Used To Classify Objects. Featuring...

3 years ago
Feature Engineering vs. Machine Learning in Optimizing Customer Behavior

 The debate on this topic is not a new one. What is the secret sauce in yielding improved modelling performance?  Is it the inputs, features or variables of a given predictive model or is it the specific mathematics that is used alongside these inputs or features? Historically, practitioners including myself, have tended to argue that it is the inputs or the feature engineering component which yield the most value when building models. In fact, I wrote a paper several years ago which was published in the “Journal of Marketing Analytics” –May, 2013 entitled “Is predictive analytics for marketers really that

To view this content
Login OR subscribe for free

Already receive the Machine Learning Times emails?
The Machine Learning Times now requires legacy email subscribers to upgrade their subscription - one time only - in order to attain a password-protected login and gain complete access.

Click here to complete this one-time subscription upgrade

Existing Users Log In
New User Registration
*Required field

Comments are closed.

Pin It on Pinterest

Share This