Descending the Right Curve in Machine Learning - A relation to science fiction and science in practice

 *  Machine Learning may appear as a magic trick to any newcomer to the  discipline - something to expect from any application of advanced scientific discovery , as similar as Arthur C Clarke , the futurist and author of popular  science fiction stories like 2001: A Space Odyssey. This sentence suggests that  ML is largely a construct of so many things combined which has the ability to deem itself incomprehensible by the sheer magnitude of the level of machinery and engineering involved which could help a general user to ascertain models and predictions based on the patterns identified from a particular dataset

*  Supporting his theory of Machine Learning , Mr Arthur C Clarke had stated in his third law stating that "any sufficiently advanced technology is indistinguishable from magic" which appeals to a common user that the when it comes to user level perception of any sufficiently high level technology , then to a common user the technology seems some form of magic . Since in magic , the trick is to carry off a spectacle without letting the viewer of the trick to get to know the underlying working principle involved in the magic

 

* Though it is greatly believed that Machine Learning's underlying strength  is some form of imperceptible mathematical , statistical and coding based magic , however , this is not a form of magic but rather one needs to understand the underlying foundational concepts from the scratch so that so of the more complex working mechanism could be understood . Therefore , it is said that machine learning is is the application of mathematical formulations to have a r great learning experience

 

*  Expecting that the world itself is a representation of mathematical and statistical formulations , machine learning algorithms strive to learn about such formulations by tracking them back from a limited number of observations .

 

*  Just as humans have the power of distinction and perception , and can  recognise what is a ball and which one is a tree , machine learning algorithms can also use the computational power of the computers to deploy the widely available data on all the subjects and domains , human beings can use the computational power of computers and leverage their wide availability to learn how to solve a large number of important and useful problems

*  It is being said that though Machine Learning is a complex subject , humans devised this and in its initial inception , Machine Learning started mimicking the way in which one can learn from the surrounding world . One can also on top of that express simple data problems and basic learning algorithms based on how  a child would perceive and understand the problems of the world or to solve a challenging learning problem by using the analogy of descending from the top of the mountains by taking the right slope of descent .

 

*  Now with a somewhat better understanding of the capabilities of machine learning and how they can help in the direction of solving a problem , one can now start to learn the more complex facets of the technology in greaer detail with  more examples of their proper usages .