We all may have probably heard the so-called word ‘Machine Learning’ or may not have but the phenomenon of machine learning blossomed on this very earth six decades before. Before diving into the topic of deep learning which is a subset of machine learning. Let’s take a glance at machine learning.
Is it Innovation of Idleness or Greediness?
The reason why machine learning came into the world is that people needed ‘Automation’ over things to achieve more production on respective things and make work and time lesser because of their greed and procrastination.
The advancement of automation has gone to a level that people started to make robotic software that does things merely as a human, recognizing their environment to work. That’s the untold logical justification behind the foundation of machine learning but as the world’s population and data incoming are getting bigger.
We are needed to rely on automation techniques to handle data but it got disadvantages such as eradicating the jobs of thousands or even millions.
Machine learning is the training of software in which data is taken and fed to a machine algorithm that based on the data fed works on upcoming tasks as humans do, where we do something and learn from it and work on further such applications. Eventually, it’s neither an innovation of idleness nor greediness but the ‘Innovation of Efficiency’.
The Need for Virtual Brain
The Human Brain has always been the most complex thing that humans ever have researched and so is its virtualization. Through Complex Algorithms and machine learning techniques, the creation of neural networks which simulate the actions and operations of neurons in the human brain enables the decision-making skill of a machine, such as finding hidden patterns in raw data and working on it without the intervention of a human being which acts as a virtual brain.
The Ultimate Innovation
Instead of learning from a pre-existing set of data, machine learning acquires data, learns from it, or trains on it before using it to make new conclusions.
Deep Learning acts like a human brain where it collects data as humans do and works on that particular data set to derive decisions or predictions that make it the ultimate innovative technology as it is a robotic software that does not need an intense amount of work, preparation, and training to work on that data as other robotic technologies do.
Since we humans are evolving the machines that we work and rely on. As the population increases the tragedy and complexity to handle the data and supplying requirements increases, As we cannot control the population of the earth which is gone rogue Already.
We’re in the need to build sources for the current and upcoming populations.
Conclusion
The world needs the help of engineers who have the solutions for it to be solved and rectified. It’s fact that the rectification and renovating are neither going to be anything near easier nor simple. The complexity increases as the data receiving and segregation of data categories increases because of the increasing population. We have to welcome aspiring engineers and support them to join in be engineering courses which are pro to invite the innovations and also for their successful future.
Author:
Ananda Krishnan PS,
II Year,
Bachelor of Technology in Artificial Intelligence and Data Science.
