A Data Science Central Community
By Bill Vorhies.
Summary: Here’ a proposal for real ‘zero touch’, ‘set-em-and-forget-em’ machine learning from the researchers at Amazon. If you have an environment as fast changing as e-retail and a huge number of models matching buyers and products you could achieve real cost savings and revenue increases by making the refresh cycle faster and more accurate with automation. This capability likely will be coming soon to your favorite AML platform.
Is there a future in which we can really ‘set-em-and-forget-em’ machine learning? So far Automated Machine Learning (AML) is delivering on vastly simplifying the creation of models but the maintenance, refresh, and update still require manual intervention.
Not that we’re trying to talk ourselves out of a job. But after all, once the model is built and implemented it’s more fun to move on to the next opportunity. If the maintenance and refresh cycle could be truly automated that would be a good thing.
Much of the effort so far has been put into simplifying getting the model out of its AML environment and into its production environment. Facebook’s FBLearner is an example of this. A number of platforms claim to ease this process for the rest of us. At least once we manually refresh the model it’s easier to update it in production.
Read full article here.