Introduction to Deep Learning and its Importance

Deep learning

Introduction

To understand what deep learning is, we first need to understand the relationship deep learning has with machine learning, neural networks, and artificial intelligence. The best way to think of this relationship is to visualize them as concentric circles:

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•  At the outer most ring you have artificial intelligence (using computers to reason). One layer inside of that is machine learning. With artificial neural networks and deep learning at the center.

•  Broadly speaking, deep learning is a more approachable name for an artificial neural network. The “deep” in deep learning refers to the depth of the network.  An artificial neural network can be very shallow.

•  Neural networks are inspired by the structure of the cerebral cortex. At the basic level is the perceptron, the mathematical representation of a biological neuron. Like in the cerebral cortex, there can be several layers of interconnected perceptrons.

•  Machine learning is considered a branch or approach of Artificial intelligence, whereas deep learning is a specialized type of machine learning.


Importance of Deep learning:




• Computers have long had techniques for recognizing features inside of images. The results

weren’t always great. Computer vision has been a main beneficiary of deep learning.

Computer vision using deep learning now rivals humans on many image recognition tasks.


• Facebook has had great success with identifying faces in photographs by using deep

learning. It’s not just a marginal improvement, but a game changer: “Asked whether two

unfamiliar photos of faces show the same person, a human being will get it right 97.53 percent

of the time. New software developed by researchers at Facebook can score 97.25 percent on

the same challenge, regardless of variations in lighting or whether the person in the picture

is directly facing the camera.”


• Speech recognition is a another area that’s felt deep learning’s impact. Spoken languages

are so vast and ambiguous. Baidu – one of the leading search engines of China – has developed

a voice recognition system that is faster and more accurate than humans at producing text

on a mobile phone. In both English and Mandarin.


• What is particularly fascinating, is that generalizing the two languages didn’t require much

additional design effort: “Historically, people viewed Chinese and English as two vastly different languages, and so there was a need to design very different features,” Andrew Ng says,

chief scientist at Baidu. “The learning algorithms are now so general that you can just learn.”


• Google is now using deep learning to manage the energy at the company’s data centers.

They’ve cut their energy needs for cooling by 40%. That translates to about a 15% improvement in power usage efficiency
















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