Overview
Machine learning (ML) is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence (AI) based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention.
Because of new computing technologies, ML today is not like the machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in AI wanted to see if computers could learn from data. The iterative aspect of ML is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It’s a science that’s not new – but one that has gained fresh momentum.
This resource is designed primarily for data scientists or analysts interested in identifying and applying ML algorithms to address identified problems.
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