There’s a lot of conversation about all the possibilities of machines learning to do things humans currently do in our factories, warehouses, offices and homes. While the technology is evolving at a rapid pace, terms such as artificial intelligence (AI), machine learning and deep learning may leave some confused. This interesting topic came to us from Information Management in their article, “A guide to understanding how deep learning works.”
The field of AI is essentially when machines can do tasks that typically require human intelligence. It encompasses machine learning, where machines can learn by experience and acquire skills without human involvement. Deep learning is a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data.
Deep learning structures neurons in layers to create an artificial neural network that can be trained to make intelligent decisions. A simple neural network takes an input and passes it through multiple layers of hidden neurons to find higher level structures. The network then uses this higher order information to make predictions for the input. Clear as mud?
The concept of making predictions based on higher order structures is important since this is one of the key things that differentiate deep learning to other classical machine learning.
Melody K. Smith
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