Machine Learning is one of the crucial members of the triad which is moving our world into an era which was only present in the science fiction stories. Combination of Big Data, IOT and Data Science is recrafting technology where impossible is the term will be used “least”
n this article, I will put a brief light on some areas where machine learning is revolutionizing the state of affairs and that are most likely to adopt machine learning like never before.
1. Cyber Security
Existing system to monitor traffic coming from outside nodes or the traffic exchanged between internal PC and servers exchanged can be defeated by the volume and variety of traffic. In nutshell, all existing IDS (information detection system) have a limit to produced alerts per unit time but the way IOT is coming up big, these limits will be insufficient to safeguard the enterprise system.
Use of Machine Learning can make Cyber Security Strategy aligned to new age threats.
2. Malware
The rate at new malware are getting generated, it will be impossible for existing tools & methods to detect all of them. The bigger challenge is the mutation of malware, where most of the new malware differ less that 2% of previous malware. This slight change in the definition of malware on a gigantic scale throws a tough challenge.
New age deep learning models are capable of fighting this challenge.
3. Legal Documents
Legal documents are very lengthy & complex to study for a normal executive unless you hire a costly lawyer, many times these legal documents are not fully studied in a belief that everything will be all right. By using deep learning and topological data analysis a complex legal document can be translated into big strings of numbers.
So the number of documents or complexity of a document can be tackled by Machine Learning.
4. Health Care
Continuous Improvement of medicines against countless patterns is a job Machine Learning can do a better. Medical experts along with Data Scientists are making a regression model to look at the relationship between independent variables that drive future events based on the hypothetical analysis that indicates the future events. The medical pattern of a person can also give lots of information regarding the future health risks.
Deep learning of these patterns can also reduce the avoidable hospitalization or emergency situations.
5. Money Laundering
Web of millions of transactions world over happening every day is throwing challenge to financial institutions and as well security agencies when it comes to monitoring bad transactions especially “Money Laundering”
With help of deep learning along with machine learning company or agency can detect fraudulent transactions from sea of all transactions.
6. Intelligence Gathering
Intelligence is gathered by many ways and one of the most important way (controversial at the same time) is surveillance. But the challenge now days is to detect and pass on the intelligence in real time. It is becoming difficult because the amount of data generated per unit time is huge and further getting bigger. Imagine a case where multiple cameras backed with data model can detect a criminal element from a crowd of thousands in a stadium or public gathering
So Machine Learning can help to make intelligence gathering effective and faster.
7. Cars
Autonomous Cars are an ideal example of how Machine Learning can revolutionize the world. Imagine an autonomous car that actually drives itself the way you would have driven. This is possible by the use of Machine learning and list goes on like AC temperature, inside lighting and so on.
Machine Learning also helps autonomous cars in a big way in other aspects of security, fuel consumption, and better maintainability.
8. Customer Service
It was impossible for an MNC to study each and customer’s behavior, likes and needs given a large number of customers it has. But with the effective use of Machine Learning, it will be possible. It does not mean that customer service has to be automated completely, but humans assisted with inputs from Machine Learning can do wonders in customer Service.