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Lisa Morgan, freelance writer who covers big data and BI for InformationWeek writes, WeekArtificial intelligence, machine learning, deep learning, neural networks. ML terms are often used , but their differences are important to understand.
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AI is seeping into just about everything, from consumer products to industrial equipment. As enterprises utilize AI to become more competitive, more of them are taking advantage of machine learning to accomplish more in less time, reduce costs and discover something whether a drug or a latent market desire.
While there's no need for non-data scientists to understand how machine learning (ML) works, they should understand enough to use basic terminology correctly.
Although the scope of ML extends considerably past what's possible to cover in this short article, following are some of the fundamentals...
Machine Learning Versus Deep Learning
Deep learning is a subset of machine learning that utilizes multiple layers of algorithms. The algorithms form neural network nodes that are arranged in three basic layers: input layer, hidden layer, and output layer. If the network has more than one hidden layer, it is considered a deep neural network.
Source: InformationWeek
