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Machine Learning April 25, 2017

Posted by Marquette MS Computing in Machine Learning.

Various forms of Machine Learning (ML) are becoming very important. Students have been reading about ML with an emphasis on unsupervised learning.



1. kevinmea - May 4, 2017

Why Machine Learning is Important

The first effect of machine intelligence will be to lower the cost of goods and services that rely on prediction. This will affect transportation, agriculture, healthcare, energy, manufacturing, and retail.  When these costs fall precipitously, there are two other well-established economic implications. First, we will start using prediction to perform tasks where we previously didn’t. Second, the value of other things that complement prediction will rise. [1]

This excerpt from the Harvard Business Review demonstrates why machine learning is important. 

First, most companies compete on cost. Removing cost from a service is one of every business’s main goals. Secondly, having predictive analytics embedded in machines removes risk from a business. Finally, using a precise machine to perform a task rather than a human will reduce risk for a business. These are all value propositions for any business in any industry to consider implementing machine learning.

The effects of machine learning are also clearly widespread, touching multiple if not all industries. The rise of home computers touched all industries and look how that revolutionized the world. We are living in the information age because of that. When machine learning becomes entrenched in just as many industries due to the positive business benefits, it might be fair to consider that to be the next age.

Safety and opportunity are the final considerations that will complement machine learning prediction. Most of the local media coverage the average public sees regarding machine learning recently is manufacturing and the replacement of human workers. Machine learning can now be programmed into robotics to perform repetitive tasks which used to be done by a human. One example of this would be sorting or picking machines. The fact is that manufacturing is often a dangerous job for a human. There were approximately 2.9 million nonfatal workplace injuries reported by private industry U.S. employers in 2015. [2] Having machine learning and predictive analytics replace human workers removes the human from the risk of injury, removes the human from a dangerous environment, and offers new opportunities for humans to work on the machines and machine learning software rather than work directly on the product manufacturing.

[1] https://hbr.org/2016/11/the-simple-economics-of-machine-intelligence
[2] https://www.bls.gov/news.release/pdf/osh.pdf

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