Here, 16 members of Forbes Technology Council share essential steps in the creation and maintenance of an effective machine learning model.

While building machine learning models is fundamental to today’s narrow applications of AI, there are a variety of different ways to go about realizing the same ends.

For the highest chances of success in machine learning, test your model early with an MVP and invest the necessary time and money to diagnose and fix its weaknesses.

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

The new machine learning model developed by Plonsky and his colleagues draws from a behavioral science framework known as BEAST (Best Estimate and Sampling Tools).

Machine learning models using step count data of the two preceding weeks were able to predict hospitalization in the upcoming week for patients during systemic therapy, but not other adverse events.