What is Machine Learning and where would you need it?

This question have startled burning me quite often from the recent days. I have started to think where to put myself to be an early bird in era of time where people believe knowledge is power in any industry. If you just google machine learning, Google’s machine learning  algorithms will help you to find the perfect Matches for your intention to knowing what is absolutely machine learning is about. Google itself is lot about Supervised Learning and Unsupervised Learning according to some experts. How does Google's automatic news Clustering may work, How does Google find the actual matches, How does Google classify pages ... may be some foods for your thoughts. Hence Google is the Man, there should be no point for me copying and pasting the same on my page. Over the news I am seeing Andrew Ng – the famous celebrity Professor of Stanford for machine learning has become himself for list of 100 most influencing people in the recent Time Magazine ranks. One could argue that Andrew contribute enormous effort to Course ERA learning – creating a new age of distance learning. However I regard this may be just one evidence that the growth of demand for the SME (Subject Matter Expertise) for the Machine learning is in pace. We see communities are gathering up on this topic at exponential rates. Well, where should I place myself then?. Why should not I place an effort to get the pace of the knowledge that the emerging community have and become kind of an early bird? I should not further be a silent observer.  100 thoughts startled to pour in to my mind in a turbulent Bernoulie’s flow. Recalling past - there was a time where people thought Genetics will change the whole paradigm of world – there will never be a food scarcity ever going to come to earth. We could either develop one pumpkin to feed the whole world. :D. So – yes there is always hundred blown imaginations on an emerging engineering filed. Fortunately Genetics did not change the world as such.  Instead with time people have started hating genetically modified food. There I remember again another wave of fad – among the Engineering or Techy, community. They said Nano Technology will change the world. It does – yes to some far. But not as revolutionary as much like the IT or Telecommunication/computer science based industry and internet. Again people say it is quantum computers which will be most revolutionary hardware thing. For me even whatever we have for the moment as a processor is more than enough to do whatever we need to get done.  But what about the human greed.  We always want to have more, do more, eat more – so process even more.

Thinking about typical human thoughts based to endless greed, when there is something found – there is always a niche, who will want to produce things in mass scale – so economies of scale, good margins, through extreme sales.  Therefore whatever the thing you discover, this niche will want to have them in mass scale. So do Data. How do you process big data and other electronic information that is in web/cloud/enterprise or what so ever? Simple – How do you search the whole web on internet and find what exactly the best solution for an identified problem.  How do you find the precise knowledge that you need from a Sea of Knowledge around the globe. There may be million solutions or even more – for one issue from different perspective. Do you think that you have time and capacity to evaluate all the alternatives and critically analyzed and found out what is best? Probably this should be the area Machine learning is looking for. One would say it is BIG data.  But above analogy is partially about data, partially about a thing we don’t know. However the famous Gartner predicts that BIG data boom is going to be ended soon like the fads we discussed before.

But, think. People thought the computers will – replace the jobs and they will reduce the jobs. I don’t know whether that has been a reality.  Instead nowadays we see lot of people working on computers. People find jobs as computer programmers, maintainers, game developers, movie developers, teller machines, billing machines etc etc. That shows that people who have the knowledge on computer are still better benefited.  Therefore for machine language learners, there should be nothing to worry about getting the new skill ready. 

My thought is this emerging field will be better used to support decision making for big projects within very couple of years. There is big part of uncertainty always associated with any kind of  project from initiation phase to the project closer. You know what - big boys are what we think for now as they will never need big losses any more. The things would include effective risk assessment, risk prediction, making made or buy decisions, whatever evaluations of projects against the risk upon probable economic trends, finding the proper places, defining the best investment portfolios, share value predictions etc etc. I have seen the enterprise scale giants have Terra bites of storage for various information about there customers. How beneficial if they could effectually use them to identify specific customer segments and possible business niches which they could know in advance otherwise? Yes Machine learning programs may already been use them for now. However whatever the application, I see this is completely about new era of accurate predictions driven decision making in either projects, or at business in general.

So remember, Prepare Today.  Yes... The algorithms are going to be hard to remember. It may be lot of tough Math inside. There are mental Barriers to overcome. There you got to do a job as well. You have limited time. The knowledge is very rare. No one to support. You will need a GPU, or need to buy sophisticated hardware. Yes true– there may be 100 limitations. But If I don’t start developing my skill today – I will never get any other opportunity here again. I l just be another observer uneasily witnessing what others do right after few years. Do you want just to be no body observing what is happening by news at 8? If not – lets start with Course Era today. Those who know the rules will play better here.