Dynamic recommenders with Bayesian exploration are able to provide more accurate and personalized recommendations than traditional recommenders. By taking into account the user’s past behavior, the recommenders can adjust the recommendations to better fit the user.
You cannot know what you do not know, until you encounter it. We put forward the question: "why not make money while you test your options?". The ecosystem.Ai Dynamic Experimentation solution will be the hot-topic case study of these discussions.
The low-code movement has swept the world, and unsurprisingly so. With innate complexities and mounting options, the complexities of making predictions work are now becoming a reality...