What Types of Machine Learning Techniques Are Used in Catalysis?
Various ML techniques are employed in catalysis, including:
Supervised Learning: Used for predicting specific outcomes based on labeled training data, such as the activity of a catalyst. Unsupervised Learning: Helps in identifying patterns and clusters in data without predefined labels, useful for exploring unknown catalytic behaviors. Reinforcement Learning: Involves learning optimal strategies through trial and error, which can be applied to optimize reaction conditions. Neural Networks: Deep learning models that can capture complex relationships in data, useful for modeling intricate catalytic systems.
