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Artificial Intelligence vs. Machine Learning: What's the Difference?

#artificialintelligence

During the past few years, the terms artificial intelligence and machine learning have begun showing up frequently in technology news and websites. Often the two are used as synonyms, but many experts argue that they have subtle but real differences. And of course, the experts sometimes disagree among themselves about what those differences are. In general, however, two things seem clear: first, the term artificial intelligence (AI) is older than the term machine learning (ML), and second, most people consider machine learning to be a subset of artificial intelligence. One of the best graphic representations of this relationship comes from Nvidia's blog.


Artificial Intelligence vs. Machine Learning: What's the Difference? - Datamation

#artificialintelligence

During the past few years, the terms artificial intelligence and machine learning have begun showing up frequently in technology news and websites. Often the two are used as synonyms, but many experts argue that they have subtle but real differences. And of course, the experts sometimes disagree among themselves about what those differences are. In general, however, two things seem clear: first, the term artificial intelligence (AI) is older than the term machine learning (ML), and second, most people consider machine learning to be a subset of artificial intelligence. One of the best graphic representations of this relationship comes from Nvidia's blog.


Machine Learning, Deep Learning, and AI: What's the Difference?

#artificialintelligence

Data scientists are expected to be familiar with the differences between supervised machine learning and unsupervised machine learning -- as well as ensemble modeling, which uses a combination of techniques, and semi-supervised learning, which combines supervised and unsupervised approaches. While it's not necessarily new, deep learning has recently seen a surge in popularity as a way to accelerate the solution of certain types of difficult computer problems, most notably in the computer vision and natural language processing (NLP) fields. By extracting high-level, complex abstractions as data representations through a hierarchical learning process, deep learning models yield results more quickly than standard machine learning approaches. Machine learning, deep learning, and artificial intelligence all have relatively specific meanings, but are often broadly used to refer to any sort of modern, big-data related processing approach.


Machine Learning, Deep Learning, and AI: What's the Difference?

#artificialintelligence

Data scientists are expected to be familiar with the differences between supervised machine learning and unsupervised machine learning -- as well as ensemble modeling, which uses a combination of approaches techniques, and semi-supervised learning, which combines supervised and unsupervised approaches. While it's not necessarily new, deep learning has recently seen a surge in popularity as a way to accelerate the solution of certain types of difficult computer problems, most notably in the computer vision and natural language processing (NLP) fields. By extracting high-level, complex abstractions as data representations through a hierarchical learning process, deep learning models yield results more quickly than standard machine learning approaches. Machine learning, deep learning, and artificial intelligence all have relatively specific meanings, but are often broadly used to refer to any sort of modern, big-data related processing approach.


Machine Learning, Deep Learning, and AI: What's the Difference?

#artificialintelligence

You hear a lot of different terms bandied about these days when it comes to new data processing techniques. One person says they're using machine learning, while another calls it artificial intelligence. Still others may claim to be doing deep learning, while "cognitive" is the favored phrase for so...