At PI.EXCHANGE, we are constantly researching and exploring new ways to make AI more accessible and user-friendly to everyone. Which is why we are excited to introduce the customer churn prediction template as the major feature in this release. With this template, we hope to put the users at ease with the repetitive and laborious data science tasks, thanks to the high degree of automation and recommendation in the template.
We believe that these updates will provide our users with an improved and more streamlined experience, while also empowering them to make more informed business decisions through the AI & Analytics Engine.
For release 1.9.0, the team is set out to:
After some intensive development cycles, we would like to introduce the customer churn prediction template. Using the template, users can simply:
Submit different datasets that are not in ML-ready format
Specify their business problem
Benefit from automatic feature engineering
Let the Engine find and run with the most suited algorithms for their data, or select some by themselves
Once users perform these steps inside a smooth workflow, they can sit back while different processes run before coming back to review models and make predictions with the following 2 options:
Make a few one-off predictions to test the model’s performance on different records from the same source used for training
Set periodic prediction schedules to predict the likelihood of churn in the future, based on refreshed transactional data that is fetched directly from the users database, and export it to the destination of choice
We still have other updates, read the full 1.9.0 release note on our Knowledge Hub.
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