Machine learning often takes inspiration from the way the human mind works. Neural networks have made huge advances in the way natural language and images are processed and attention models – which mimic human behaviour to some degree – are gaining prominence. In simple terms, attention models selectively process data by focusing on the parts or segments of data that is the most important. Just as the human mind focuses on important facts when evaluating a situation, attention models speed up the processing of large volumes of data by concentrating on the most relevant segments. The data science applications for attention models are broad and rapidly evolving.