Stop tuning your model and use the results

Hey, tuning models and running ensembles is really fun.  So fun, that it is hard to stop and remember what problem you were trying to solve in the first place. You have to remind yourself that the problem you are trying to solve is not addressed until you do something with your results. Depending on the type of problem you are trying to solve, the presentation of results will be very different. A handy template I use to present machine learning results in presentation or report form is: 1. Context (Why). 2. Problem (Question). 3. Solution (Answer). 4. Findings: (Results and Interesting Discoveries). 5. Limitations (What the results can’t do). 6. Conclusions (Why+Question+Answer). Putting a model into operations is a serious undertaking. It typically can mean a re-implementation of the algorithm tailored to the problem and the operational environment. It also requires testing, back-testing, tracking and even ongoing updates. Discover more about how to best present your machine learning results in the post:     >> How to Use Machine Learning Results I'll speak to you soon. Jason. To make sure you keep getting these emails, please add [email protected] to your address book or whitelist us. Want out of the loop? . Our postal address: 151 Calle de San Francisco, Suite 200 - PMB 5072, San Juan, PR 00901