Data Science = Insights
Machine Learning = Prediction
Artificial Intelligence = Actions
Data Science produces insights
The primary difference of data science from machine learning and artificial intelligence is that it requires humans to understand the insight and to interpret the data. Data scientists could use tools and visualize data, but ultimately they are trying to get a better understanding of the data that they work with.
Machine Learning is the field of prediction.
Machine learning is a set of algorithms that train on a data set to make predictions or take actions in order to optimize some systems. Machine learning is coined by Arthur Samuel in 1959 when he realized that rather than teaching machines all that they need to know, it would be a better way to have them think like humans without all the weaknesses that humans have.
Artificial Intelligence produces actions
Artificial Intelligence is classified into applied or general groups. Applied Artificial Intelligence is AI that is focused on performing one action such as a system designed to trade stocks or to analyze how safe driving patterns are. Applied Artificial Intelligence is designed for solving particular kinds of problems. General Artificial Intelligence is a system or device that can handle any tasks. However, this type of AI isn’t as available today, as the technology for it is still in our distant future.