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Vol.2, Issue-41, November 2016
Published by:-Chitkara University

Machine Learning

"A breakthrough in machine learning would be worth 10 microsofts" – Bill Gates

It is no surprise that when you purchase or simply browse any product on any ecommerce website you start to see ads related to that product all over while you surf the internet. Thanks to machine learning!

Machine Learning is a field of artificial intelligence where machine (computer) learns on its own without being explicitly programmed, or in other words the computer program is such that it changes (or adapt itself) on its own upon receiving new data. A device undergoes various iterations and finally behaves independently based on its past experiences (or instances). Machine Learning is one of the few technologies which are changing the world around us rapidly. Most of the Disruptive Companies belonging to e-commerce, social media, search engines that are purely led by innovation are using Machine Learning algorithms to outsmart their competition.


For example Google uses Machine Learning Algorithms to find out what are the things people click the most on the internet; Amazon uses Machine Learning Algorithms to add features on their site about product recommendations to build a smart recommender system; Facebook finds people whom we want to connect with using Machine Learning. These are just a few popular examples, there are a tons of applications where Machine Learning is employed. It is one such technology that optimizes the work. People from all field of engineering are getting into this interesting area.

How Machine Learning Works?

In this you fed data to machine learning algorithm, the algorithm interprets the data and gives the analysis in the form of graph, charts or any statistics. It collects data, images and other statistical inputs, combines its deep learning algorithms such as regression, classification and builds a smart & intelligent application. Machine learning can be learned & implemented through various software tools available in the market today, some of these tools are - WEKA, Graphlab using IPython notebook.


How Machine Learning Works?

As indicated earlier there are tons of applications where machine learning algorithm are used to make intelligent technology applications. Some of the examples are as follows:-

Personal Health Monitoring Device- There is a device which can keep track of the health of a person. It should be worn by a person all the time. Based on the day-to-day activities of the individual, it collects data such as sleep hours, standing time, walking time, exercise time; it analyze & interpret the data using machine learning algorithm and tells that how is health of the individual evolving over a period of time. With this device one can keep track of his/her health.

Face Detection-Face Detection feature in digital camera is an application of machine learning wherein the camera automatically takes a photo upon detection of face.

Anti-virus - Machine Learning Algorithms are used in anti-virus for detecting malicious software on computer devices.


By - By Shaminder Kaur – Asst. Prof. ECE, Chitkara University Himachal Pradesh


About Technology Connect
Aim of this weekly newsletter is to share with students & faculty the latest developments, technologies, updates in the field Electronics & Computer Science and there by promoting knowledge sharing. All our readers are welcome to contribute content to Technology Connect. Just drop an email to the editor. The first Volume of Technology Connect featured 21 Issues published between June 2015 and December 2015. This is Volume 2.
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Disclaimer:The content of this newsletter is contributed by Chitkara University faculty & taken from resources that are believed to be reliable.The content is verified by editorial team to best of its accuracy but editorial team denies any ownership pertaining to validation of the source & accuracy of the content. The objective of the newsletter is only limited to spread awareness among faculty & students about technology and not to impose or influence decision of individuals.