Machine learning (ML) algorithms can analyze vast amounts of data to identify trends and make predictions. In catalysis, ML can be used to predict the performance of new catalysts, optimize reaction conditions, and even discover entirely new catalytic materials. For example, regression models can predict reaction yields based on various input parameters, while classification algorithms can help categorize catalysts based on their activity and stability.
