Scope of Machine learning and its Applications
Origin of Machine Learning and its Scope
Machine learning is an attribute of Artificial intelligence and a tool which performs tasks without any explicit command or instruction through mathematical modeling.
Machine learning is believed to be born in the 1950s with overall of probabilistic and statistical possibilities only.
By the time the computational abilities increased, and digital dependency has become dominant and necessary as well, its purpose and requirement both, got a reason and scope respectively.
Its applications are numerous, including almost every sector nowadays.
As far as its frequent use is concerned, Home appliances, automobiles, machinery hardware especially related to industries for manufacturing are those which had adopted ML as their tool to work with on a daily basis.
Apart from that, there are a handful of other applications as well, which may not look obvious for Machine learning but sound sensible and are really helping us in a large manner. And those include-
● Finance- Governments nowadays are firmly relying on this tool, to predict the future growth of a state or country itself, by putting previous year data for subsequent years.
The process became very simple to presume a tentative GDP for the upcoming years by putting all the necessary statistics responsible to build a nation economically weak or strong or GDP precisely.
● Arts- ‘Computational creativity’ is something that has just crossed the expectations of a human from a computer.
Generally, a computer is expected to perform a calculation or to represent a man-made art digitally. But, computational creativity is a fruit of Machine learning which is capable of giving a new taste.
Through ‘Computational creativity’, you can even create a new melody or music composition of a specific tempo and genre on the basis of previously stored data of incomplete music records which are yet unused.
● Face & Voice Recognition- This application of Machine learning is one of the most used applications being used for security purposes. Not only confined to the security agencies but the social media applications are also possessing this feature.
● Disaster Management- This is an explicitly profitable application for public interest because the most chaotic calamities are going to be predicted with the help of machine learning, there are thousands of lives that can at least be prepared for them.
Machine Learning or Human Brain?
To understand the hows and whats of ML, a human brain can be considered as a model. Which would be funny because the most unveiled and mysterious organ of a human body would become a model to understand something.
But that is strongly relatable as well because Machine learning is a process of feeding the data, implementing the data, keeping that activity in memory, and improving the result at next attempt.
All that is for which we rely on our mind and blame it for any blunder we make.
We code a machine, and it functions accordingly. Similarly, we merely realize that our mind is not responsible for what it shows, but it shows what we fed into it. And there is no sense in abusing our mind for its non-functioning.
It is all about consistent and appropriate data feeding whether it is a machine which possesses Machine learning or a human brain.
The learning process is theoretically unavailable for a human brain, but some psychologically proven facts like a 21-day cycle tell us how a human brain adapts a habit and how much time it usually takes to become a schedule.
However, Machine learning would not take 21 days to learn but it is strictly dependent on enormous data to become functional.
Machine learning maintains a sisterhood with the most powerful tool of AI today i.e. ‘Deep learning’ and is envisaged as the future of the 21st century. Often misinterpreted as software also but actually, it is a tool.