How Do Machine Learning Algorithms Differ From Traditional Algorithms?
Machine learning is an algorithm or model that learns patterns in data and then predicts similar patterns in new data. For example, if you want to classify children’s books, it would mean that instead of setting up precise rules for what constitutes a children’s book, developers can feed the computer hundreds of examples of children’s books. The computer finds the patterns in these books and uses that pattern to identify future books in that category.
CMSWire’s Top 10 Artificial Intelligence and Machine Learning Articles of 2018
As we move into 2019, two things remain on all our minds: how did the year pass by so quickly, and how long will it be before artificial intelligence conquers the world and subjugates humankind?
I jest of course, but even when we put our fears of the unknown aside, the rapid development of artificial intelligence and machine learning technology is nothing to scoff at.
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Computers may not wear tennis shoes (yet), but thanks to developing artificial intelligence technologies, they’re smarter than ever before. Along with those technologies has come a relatively new category of computer science called machine learning, or ML.
Similar to statistics, ML involves computer systems that utilize algorithms to automatically learn about data, recognize patterns, and make decisions, all without outside intervention or explicit directions from human beings. In the real world, you can find it being used in smart assistants like Siri and the Amazon Echo, in online fraud detection services, in the facial recognition feature that identifies photos of you on Facebook, and more recently, in Tesla’s self-driving car.