5 Surprising Machine Learning Applications

Today, machine learning is in every corner! From Google Home and Amazon Echo to self-driving cars, machine learning has divulged so many smart applications. We possibly couldn’t have thought of these applications even a decade back.

Think about it, how we would have lost directions if GPS were not here to help us find our way? Things were so hard when Uber was not there to drive us from place to place. In between all these great applications and uses of technology, machine learning has a big role to play.

“Alexa, turn on the lights”

“Alexa, order a pair of socks from Amazon”

Machine learning has made it all so much easier and better.

Here are some of our favorite applications of machine learning.

5 Mind-blowing Machine Learning Applications

1. Predicting Flight Risk

It is crucial for the court to decide whether to allow a person to stay at home during the trial or put them in jail. It eats up government resources, and if the person is not guilty, it puts an innocent man through jailing unnecessarily. However, not jailing a guilty person can motivate them to commit yet another crime or flee.

A group of scientists found an algorithm which can access the flight response of a convict. When it was tested in some cases, the results outperformed the judgment of many experienced judges.

2. Forming A Link Between Psychopathy and Twitter

Have you ever read someone’s twitter feed and felt odd?

Now, machine learning can tell you if any individual is a psychopath just by analyzing their twitter feed. This machine learning data suggests that there is some link between patterns used by psychopaths which can be identified through machine learning algorithms. A strong correlation has been found in psychopathic tendencies and language words such as hate, we, I mean, um, etc.

3.  Avoiding Risk of Money Laundering

Various companies that offer online transactions are always on the lookout for money laundering. These organizations often hire analysts to see the good and the bad situation to evaluate money laundering cases effectively. However, just like other manual processes, this one is also imperfect and affected by human errors.

Hence, PayPal made a machine learning algorithm to detect money laundering cases with efficiency. The accuracy of detecting fraud is higher and human mistakes are reduced.

4. Predicting Occurrence of Earthquake

Many people get injured, lose their homes, and die because of earthquakes. Predicting its possibility can save so many lives. So, a group of scientists developed a machine learning algorithm and trained it to learn how an earthquake will sound before happening. This can predict many future earthquakes with amazing accuracy and help in saving many lives.

5. Improved Cyber Security

Cybercrime costs are predicted to reach USD 6 trillion per year by 2021. Clearly, organizations are at risk of falling prey to online predators. The data of your organization can be stolen, and important information such as credit card details can be misused.

Hiring human employees to fight against cybersecurity has its share of errors and loopholes, as humans can be influenced by emotions. Further, humans can’t work all day long. But, machines can, which is why machine learning algorithms are now helping in keeping cybercrimes at bay.  The defense mechanism of these algorithms can accurately judge phishing attacks and protect the organizations against suspicious activities.

Conclusion

As machine learning models and algorithms gain more popularity, this technological advancement will bring forth many more new, highly useful applications. No doubt, machine learning has the power to change so much around us. From being able to optimize social media to customer support, there are so many more applications of machine learning that we experience every day. Surely, artificial intelligence and machine learning are expected to change the world we see today.

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