When it comes to machine learning versus data science, it’s helpful to know the differences and where to find common ground.
Who better to ask about artificial intelligence (AI) than the current darling of the scene, ChatGPT? Its answer (‘Machine learning and data science are closely related fields, but they are not the same thing’) is a useful starting point. But unpacking the differences between machine learning versus data science requires human effort, for the time being at least. Until the machines take over.
Business machines play checkers
If you are new to machine learning, it’s worth skipping back to the late 1950s to gain an understanding of its origins. During this time, Arthur Samuel – a computer scientist working for IBM in the US – popularized the idea of machines that had ‘the ability to learn without being explicitly programmed to do so’. A good illustration of this was the checkers-playing computer devised by Samuel. At the heart of the machine, was a search tree algorithm capable of exploring possible states within the game and selecting the one with the greatest reward.