Several ML techniques are employed in the field of catalysis, including:
Supervised Learning: Used for predicting specific outcomes based on labeled training data. Unsupervised Learning: Helps in identifying patterns or groupings in data without pre-labeled outcomes. Reinforcement Learning: Optimizes catalytic processes through trial and error to maximize rewards. Neural Networks: Mimic the human brain to recognize complex patterns and relationships in data.
