General discussion : Generative AI
During this session, participants will understand how to use our AI software to create a real-time recommender that delivers personalized recommendations to users based on their behavior and preferences.
Making customerized recommendations using ecosystem.Ai. Understanding how to adjust the new knowledge parameters to customerize your recommendations.
During this session, participants will understand how to use our AI software to create a real-time recommender that delivers personalized recommendations to users based on their behavior and preferences.
Making customerized recommendations using ecosystem.Ai. Understanding how to enrich transaction data to make customerized recommendations.
During this session, participants will understand how to use our AI software to create a real-time recommender that delivers personalized recommendations to users based on their behavior and preferences.
Making customerized recommendations using ecosystem.Ai. Understanding how to use and adjust the Ecosystem Rewards algorithm to make customerized recommendations
During this session, participants will understand how to use our AI software to create a real-time recommender that delivers personalized recommendations to users based on their behavior and preferences.
General discussion : Responsible Use of Data and AI Technology
During this session, participants will understand how to use our AI software to create a real-time recommender that delivers personalized recommendations to users based on their behavior and preferences.
Practical applications of Bayesian regression with ecosystem.Ai
Bayesian regression is a statistical method used to estimate the relationship between variables. It uses Bayesian inference, which is a form of statistical inference that relies on probability theory. In Bayesian regression, the relationships between variables are estimated through data rather than through assumptions.
Incorporating Customer Feedback for Better Predictions
Responding to customers requires an understanding of the ever-changing human contexts in which they exist. It is important to remain knowledgeable and aware of current trends, industry changes, and the needs of customers. We will discuss methods of monitoring customer responses to experiments using dashboards and activating further dynamic experimentation in ecosystem.Ai.
Dynamic Experimentation for Customer Recommendations in Real-Time
Dynamic experimentation for customer recommendations in real-time is an innovative approach to providing customers with tailored recommendations based on their individual preferences. ecosystem.Ai uses a combination of machine learning and computational social science to predict customer behavior and provide personalized recommendations.