Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to
become more accurate at predicting outcomes without being explicitly programmed to do so.
Machine learning algorithms use historical data as input to predict new output values.
Recommendation engines are a common use case for machine learning. Other popular uses
include fraud detection, spam filtering, malware threat detection, business process automation
(BPA) and predictive maintenance.
Types of Machine Learning
Classical machine learning is often categorized by how an algorithm learns to become more
accurate in its predictions. There are four basic approaches: supervised learning, unsupervised
learning, semi-supervised learning and reinforcement learning. The type of algorithm a data
scientist chooses to use depends on what type of data they want to predict.
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