Published by Bill Crawford,
By Shuvro Sarkar
One of the latest trends in the world of technology and engineering is “machine learning” — in fact, all of the big technology companies today have invested in artificial intelligence and machine learning projects.
The term “machine learning” was first defined by Arthur Samuel, way back in 1959. He defined it as “the ability to learn without being explicitly programmed,” which basically means that a machine could learn from its own mistakes and reprogram itself to improve its performance over time.
The idea gained popularity in the 90s when the concept of data mining came into existence. Data mining uses algorithms to look for patterns in a given set of information, which led to data-driven predictions and decision making. This encouraged engineers to develop complex machine learning algorithms by making use of data mining and predictive analytics.
Innovations that are driving business advantage
Today, machine learning algorithms are already being used widely in various ways. Here are some, everyday uses of machine learning that you probably didn’t know.
Machine learning becomes mainstream
The technology is advancing at a rapid pace as we continue to find new ways of using machine learning. Enterprises too, are keen to get a hold of machine learning for the betterment of future products and accomplishment of strategic goals.
Machine learning brings value to all the data that enterprises have been saving for years, by churning high volumes of data and helping gain deeper insights and improve decision-making. The figure below depicts some of the applications of machine learning across multiple industries.
Future application to use machine learning
Machine learning algorithms are being used extensively to re-engineer business processes such as sales, marketing, logistics, procurement etc. across industries. The beauty of it all is that these algorithms keep getting better with time by itself.
The real reason behind this accelerated adoption of machine learning is that the algorithms are iterative in nature, repeatedly learning and probing to optimize outcomes. Every time an error is made, machine learning algorithms correct itself and begins another iteration of the analysis. And all of these calculations happen in milliseconds making it exceptionally efficient at optimizing decisions and predicting outcomes.
Machine learning makes it easier to devise sophisticated software systems without much human effort. Instead of spending years coding features or fine tuning a system with a lot of parameters, we can use machine learning to get done in a much shorter time span. Don’t be surprised if you soon begin to see and use technology and gadgets, which is as of now seen in science fiction movies.
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November 10, 2016 at 02:04AM
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