Machine learning is a type of artificial intelligence (AI) that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can change when exposed to new data.
The process of machine learning is similar to that of data mining. Both systems search through data to look for patterns. However, instead of extracting data for human comprehension -- as is the case in data mining applications -- machine learning uses that data to detect patterns in data and adjust program actions accordingly. Machine learning algorithms are often categorized as being supervised or unsupervised. Supervised algorithms can apply what has been learned in the past to new data. Unsupervised algorithms can draw inferences from datasets.
A sweet spot for machine learning is online recommendation engines, highly visible to users of Amazon, Netflix and other websites. Other common uses include fraud detection, sales forecasting, predictive equipment maintenance, programmatic online advertising and price optimization.
Facebook's News Feed uses machine learning to personalize each member's feed. If a member frequently stops scrolling in order to read or "like" a particular friend's posts, the News Feed will start to show more of that friend's activity earlier in the feed. Behind the scenes, the software is simply using statistical analysis and predictive analytics to identify patterns in the user's data and use to patterns to populate the News Feed. Should the member no longer stop to read, like or comment on the friend's posts, that new data will be included in the data set and the News Feed will adjust accordingly.
Beyond personalized marketing, other common machine learning use cases include network security threat detection and predictive maintenance fueled by data collected via the internet of things (IoT). In a more offbeat vein, recent projects have involved the use of AI in creative endeavors, including songwriting and fashion design -- initiatives that highlight the flexibility and overall processing power of machine learning technology.
See also: deep learning
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