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What is machine learning?

Machine learning is one of the most exciting technologies as it brings computers closer to human beings with the ability to learn. It is a field that lets computers learn without having to be explicitly programmed. The basic concepts of machine learning are representation, evaluation and optimisation.  

For a better understanding, let’s look at an example. 

Think of a student who is studying for his exam. His brain is the machine and he is feeding it with his course materials that are the input to understand the subject better. While giving the exam, his brain logically solves the questions because he has learnt the subject well. That is how exactly machine learning works. The computer learns from experience and starts to notice similar patterns to logically implement them in the required situations. 

 

History of machine learning 

In the year 1958, the first-ever artificial neural network called Perceptron was developed by Frank Rosenblatt aiming at shape and pattern recognition. Two more models were developed at Stanford University by Bernard Windrow and Marcian Hoff. the first model could detect the binary patterns and was called ADELINE.  The other one was called MADELINE that has a very real-world application to eliminate the echo of phone lines and is in use even today. However, this did not have a lot of progress till the 1970s because of the wider population of the Von Neumann architecture which was relatively simple to comprehend and so was used by a lot of people. 

During the 1980’s and 1990’s, there was a spike in the interest in neural networks. Japan announced its focus on advanced neural networks, pitching in American funding leading to deeper research. In 1986, three researchers took forward the Windrow and Hoff research at the Stanford Psychological department and modified it. 

In 1997, the world chess championship was won by the chess-playing computer IBM computer deep blue

In 1998 AT & T laboratories researched digit recognition and showed satisfactory results of detecting handwritten postcodes od US postal services.

The advent of 21st century made the business realise that the calculation potential can be increased with the help of machine learning. Large projects like Google Brain (2012), Alex Net (2012), Deep Face (2014) Open AI (2015), Amazon learning platform (2015), U-Net (2015) and many more. 

 

How does machine learning make life smarter? 

In this world, where it is almost impossible to live without our electronic devices. Machine learning is a blessing as it helps our devices understand us and our needs better. It optimises and personalises our entire online experience. 

Let us take a few examples to understand how it will make our life smarter. 

For instance, you want to remodel your bedroom and for that, you have been surfing various sites for the kind of furniture you would prefer. Your phone has kept a track of the kind of furniture you are trying to find and this helps it to understand what style of design you like. The next time you open Pinterest it would show you interior design ideas of that same style which could help you get a better idea. 

Another example would be you have decided to cook biriyani for lunch and you are trying to google recipes, you would then start getting notifications from food delivery apps about the best deals on biriyani. 

There are several ways how machine learning will enhance our life, gaming can be transported to another level of intelligence altogether, peeking into the future automated transport and cyborg technology isn’t too farfetched given the advancements in the field of machine learning.

It would also protect humankind from dangerous jobs like bomb diffusing and could also contribute hugely to environmental protection. It can give rise to enhanced and improved health care and smart homes. Machine learning can do wonders to upgrade and refine our lives. 

 

Career scope of machine learning 

There is a huge demand for AI professionals as every enterprise irrespective of the size of the organisation as it is a crucial department. To possess a skill set of machine learning, there is a requirement of a lot of dedication along with a deep understanding and passion for coding. However, if you have mastered the skills of machine learning it opens up a whole new horizon of potential jobs. Some of them are, machine learning engineer who is responsible for designs and implementation to decipher the meaning.  Data scientist has the responsibility of collecting, analysing and interpreting a lot of unorganised data and they too have a high demand in the professional world. Career opportunity as a data architect is also well celebrated and they are supposed to develop, construct and maintain high scale data. 

These are all good career choices if you are fluent with coding and numbers, they promise a good pay check and job security. 

 

Future scope of machine learning 

The future of machine learning seems quite bright as there are endless possibilities that the advancement of machine learning will bring out. 

Machine learning can make our childhood dream of living in a world with robots come true as vision, grasping, motion control and data in robots is possible because of machine learning. 

It can help difficult concepts like quantum computing sound easy because it eliminates the hard work of manually computing the data rather machine learning does all the work very quickly giving out results and  saving a lot of time and effort that could be channelled elsewhere. 

Frauds can be prevented as they keep a track of the patterned behaviour and any unusual activity shall immediately give rise to suspicion which will create alertness among the officials and prevent frauds. The biggest advantage of machine learning to the public will be the personalisation of data, with busy lives each day people have to make an extra effort to search for the things they need and with the evolvement of machine learning this is will be solved as it keeps a record of the user’s needs and gives them information according to it. 

All of this paves way for a promising future of machine learning. 

 

Conclusion 

Machine learning is all about understanding optimisation techniques and unknown patterns in data automatically to simplify the entire concept. It needs more attention and should be brought more into light in front of students who possess all the required skill set but are confused of what they should choose. If given the right amount of funding and recognition, machine learning can do wonders proving that this concept has no limits and positively contribute to the welfare and economy of the nation. 

 

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