Machine Learning Is Everywhere

By Balachander Ramachandran on November 10, 2014


 In 1959, Arthur Samuel defined machine learning as a “Field of study that gives computers the ability to learn without being explicitly programmed.” Although it has been around for a long time now, Machine Learning is becoming more prevalent now. Most of us have encountered it without even realizing it. From  recommendations to search engines, from self-driven cars to intelligent personal assistants, they are all the byproducts of applying Machine Learning techniques to solve  real world problems. Now, Machine Learning is everywhere!

 There are two components to this evolving field. The Algorithms or the statistical modelling and the Implementation. When we have meaningful data with labels, it is a task for supervised learning. It is more challenging to do the same for un-labelled data which falls under unsupervised learning. What was once a technology used by few elite organizations has now infiltrated many industries, startups and other organizations.

One of the chief reasons for such a widespread use is the advancement in computing and the huge explosion of data available online (thanks to growing popularity of the Internet). With the emergence of BigData, Machine Learning provides the best way to exploit that opportunity.


We being creatures of habit, one can always find patterns imprinted in our behavior. It is precisely this phenomena that many techniques in Machine Learning exploit to predict one’s actions in the future. It is all the more relevant in medicine, where processing these patterns leads to a better, or an early, diagnosis and thus improve the quality of health care. It can be used to solve some real world problems like analysis traffic patterns at an intersection to predict when a given street will be busy, tracking user behavior to provide better recommendations, etc.

As Martin Hack, the CEO of Skytree put it:

“In a way Machine Learning has become the new black gold. The application areas are literally endless and from where we stand we haven’t even reached the inflection point. If you think about it, there are many industries out there that are just waking up to the reality of big data and data science.”

It has already become the rock that will provide the foundation for many cool things in the future.

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