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Machine learning is about the application of human cognitive like capabilities via artificial neural networks to essentially bring sophisticated mining techniques so that you can decipher patterns, uncover insights and be able to guide actions to create exponential impact.

If you take the evolution that we have been observing, we now have the ability to script and automate through BOTS and our PA. The basic tasks that we, as knowledge workers, have been undertaking, which is leading to a dramatic improvement in efficiency as well as productivity but, the next step that we are already starting to observe and where we are going to be pivoting to, is beyond automation.

This is not all. The ML has also been quietly working in the background for years, powering mobile apps, search engines and lots of other things but now, it has become a widely circulated buzzword and expanding its reach amongst various arenas and, affecting businesses as well. So, while mapping out the strategies for your organization, it’s very necessary to consider on the technology, societal influences and learning science for making sure that you have a targeted, scalable strategy, which will let you achieve organizational goals. Let’s check out the latest Machine Learning Trends to Watch IN Coming Years that should be on your radar?


Now, the tech giants such as Amazon, Google, IBM and Microsoft are increasingly putting their focus on bringing ML (machine learning) technologies at disposal of the developers in each country and organization all over the world. In the year 2015, one of the biggest tech giants Google’s Brain team develop an open-sourced TensorFlow (a software library used for machine learning like neural networks).

Amazon launched its DSSTNE- pronounced “Destiny” (Deep Scalable Sparse Tensor Network Engine under the Apache 2.0 license on GitHub. The Elon has developed an Open-Artificial Intelligence (AI) (a non-profit research company that promotes and develops friendly AI to benefit humanity). In the year 2010, IBM launched the Watson Analytics (a machine learning framework having the capabilities of cognitive computing).

These open libraries for the software developers are destined to make sure the contribution of coders in ML. These resources coupled with cloud computing are enabling several small organizations and individuals to learn and use these trendy technologies. These tech giants are doing their best to make the sure the democratization of ML technologies by scaling up the number of the users of the Machine Learning.


Though, we know that we are capable of counting the number of competitive cloud solution providers on our fingertips but, we cannot be so sure that we will choose the best solution. Currently, we have tech giants such as IBM Watson, AWS (Amazon Web Services), Google Cloud Platform and Microsoft Azure. Well, they all are the biggest players of their field but, for the beginners, it is difficult to choose the platform in the arena of Data Science that can complete their needs in the long run.

With the increasing usage of ML, the competition in the strategic marketing across several platforms will be increased and the race to launch new inventions as well. At present, it is clear to see the competition between the tech giants in showing their strengths but, we can be sure that there is more to come.


The job that will see the highest demand in the future is Data Scientist. It is already in-demand and by the time passes, it will go to skyrocket. A wide skill gap between the market potential and the needed skills will give peace to the geeky group of developers while bringing a hard time for the below average coders. Due to this trend, the academicians will also be required to figure out that what courses should be filled into fill-up the gap between the ever wondering demand and supply gap. Also, in the lack of an apposite framework for education, the hiring problems will remain to escalate.


In the software procedures, the RPA (Robotic process Automation) is the automation of rules based tasks that include CRM procedures and data entry jobs and so on. It is being estimated that this automation will be gaining more and more users with the day-by-day increase in cognitive abilities and more impactful ML algorithms along with the data sets. ML in a collaboration with the AI is gradually about to take over the manual routine jobs all over the industries.


As per the research, done by one of the biggest global management consulting company Accenture, an average company is being affected by the 106 targeted cyber-attacks per year. As we all know that cybersecurity plays a highly important role in each and every business and is the major concern for all the companies all over the world. We all know that it is not easy to solve the cyber attacks issues but we can surely acquire the better security if we train our systems to learn from the previous brute forces. And, the ML works on both sides. If it is used by the potential hackers, it has the ability to result in the powerful attacks but if it is used by firms, then it can expand the level of the security as well.

Okay now, we have discussed the Machine Learning trends that we will see in the coming years. From the small-sized companies to the large-sized MNCs are having the capability to channelize the Machine Learning utilizing the cloud computing at the cost incurred in developing those systems. To get more updates about ML, stay tuned.

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