Advantages of Machine Learning

Hello GOOGLE!

This is what android users say to their virtual assistant when their hands are already equipped with some work, and they want someone to assist them with it.

Siri and Alexa also assist users in their own ways, but has it ever struck you, what is this magic spell? This is the charm of machine learning. The term ‘machine learning’ was coined by Arthur Samuel, an American computer scientist, in 1959. It is a subset of artificial intelligence and is one of the most useful and powerful technologies used worldwide. It refers to a system’s ability to learn with experience and produce conclusions out of events. These conclusions guide the system as it discovers its way through a problem. It is much like how human beings learn – it applies a technique to a task, and finds the flaws in it. The findings are then used to correct the next attempts on a similar job.

In 1997, IBM’s chess engine named Deep Blue defeated Gary Kasparov, the reigning world champion. It was a significant breakthrough showcasing the power of machine learning, and it never went downhill from there. It is now in use in most of the sectors of industries, directly or indirectly.

The most important use of machine learning is to convert a given piece of information into usable knowledge. Some primary applications of machine learning are observed in tasks related to prediction, image and speech recognition, and medical diagnosis. You can witness its magic in our day to day lives without being noticed by us. It can be categorized into following forms

• supervised
• unsupervised
• semi-supervised
• reinforcement learning

With the broad scope of application of machine learning, comes several advantages. These are -

• Machine learning is automatic; i.e., it doesn’t require human intervention to make decisions or to work smoothly. Once a learning program is initiated, it learns the results of different possibilities by itself. It does not require any additional inputs by humans, and can independently make decisions of its own. A valid example to support this is an anti-virus program, which has the ability to recognize and eliminate new threats, which might not have been introduced during its development.
• Machine learning helps us to get our work more effectively and efficiently. It helps in better decision making and provides more accurate results to the users. For example, chess grandmasters use chess engines that run on machine learning to train themselves for their games.
• Machine Learning algorithms are good at handling data that are multi-dimensional and multi-variety, and they can do this even in an uncertain environment. This can be witnessed by observing the computers built for the purpose of weather forecasting, which is a highly complex and dynamic phenomenon.
• It helps people to work better as it helps to identify patterns and trends effortlessly. For example, in the case of digital voice assistants, that observes what a person uses the most on their device and optimizes itself so as to make it handier for its user. Another example is e-commerce websites. These websites obtain data of what you search for and see the most, to recommend you items that suit your buying habits.

It has been shown time and time again that machine learning is a field of high potential and carries the ability to revolutionize many areas of research. The effortlessness in its working pattern has a complex structure behind it. Penetrating and breaking the complexity requires a strong educational foundation that is taken care of in many top engineering colleges in India.

As of now, it is very clear that it is going to become more important in the near future, as many more of its applications and potencies are yet to be discovered.