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Data makes promising scope of Machine learning

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Rachit Jain, CEO, Youth4work

02-Jun-2018

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Articles
The number of Indian Machine Learning Start-ups is on the rise. On an average 10 to 15 such new tech start-ups are seen every month, with each claiming to be better than the other. But the success of a new tech start-up cannot be ensured by mere sophisticated AI tools and applications. Having data is essential and acquiring reliable data takes time and effort if done with right ethical practises unlike Cambridge Analytica.

Machine Learning- A term that was coined by Arthur Samuel in 1959 is creating a lot of fuss in the present time. As to why is not very hard to say, machine learning has been a buzz word in India for quite some time now. But what it really is and how it really works is altogether a different story that remains out of grasp for many. 

 

If the current perception is to be believed then Machine Learning seems to be synonymous with AI, Artificial Intelligence and more often than not these two terms are used interchangeably. Also, these two ultra-sophisticated terms bring high cachet to the table, especially when an argument regarding technology is involved. But the truth is that machine learning and AI are two different subjects. In layman’s terms, AI aims to make machines smarter by giving those capabilities to think on their own feet to make decisions or mimic human actions whereas machine learning is just a sub set of the vast concept, that is, AI.

 

The most crucial aspect of machine learning is Data. Without data it is not possible. Data is the backbone of ML. Machine learning is an application of and within the AI that provides computers with the ability of learning and to improve from experience without being explicitly programmed. Data is used by the machines to create patterns that make sense to them. Data by itself is useless, unless it is treated in meaningful ways and machines can perform unimaginable tasks with data using mathematical algorithm and block chains.

 

The number of Indian Machine Learning Start-ups is on the rise. On an average 10 to 15 such new tech start-ups are seen every month, with each claiming to be better than the other. But the success of a new tech start-up cannot be ensured by mere sophisticated AI tools and applications. Having data is essential and acquiring reliable data takes time and effort if done with right ethical practises unlike Cambridge Analytica. Giants like Google, Amazon, and Facebook took years to accumulate hoards of data and their data is used by many other emerging tech enterprises that are looking for shortcut successes. Such enterprises won’t last long in the long run because machine learning will only prove to be beneficial if the end results are insightfully unique and this can only be ensured with the authenticity of the data so used.

 

Nonetheless, scope of machine learning cannot be overlooked, especially in the fields of education and recruitment processes. There have been some promising start-ups in recent times that have dedicated and devoted themselves, over the years, in providing youth with the much needed “job-specific skills” that are essential to survive and sustain growth in a highly volatile job market of the present.

 

A recent survey by Youth4work analysed that more than 35% of India’s Youth is unemployed, which is even lower than the average of global employment level. According to figures projected by the survey report, our country will see a marginal stagnation in 2018-19. As of now, 17.9 million are unemployed and this estimate will further expand to 19 million in 2019.