Uses of Machine Learning You Should Know About — Have you ever wondered what good is Machine Learning and what it can be used for? Already ML is used by various industries, from medicine, to data security to personal security and every day more and more businesses find a use for Machine Learning. Here are 10 uses of Machine Learning:
1. Online search
Knowingly or unknowingly, but we meet with Machine Learning almost every day when we go online and search something on Google. Every time you search for something, Google’s search engine learns from your actions. Did you click on the website you’ve been presented? Than the search engine has done its job. Have you clicked away? The search engine still needs to learn.
2. Fighting malware and spam
Everybody hates malware and spam. However, today there’s so much of it that humans simply can’t keep up. This is where Machine Learning and also Deep Learning come in to help you fight these online menaces. For instance, Google uses its own neural network to fight spam by getting data from Gmail users and learning from that. If users consider something to be a spam, then Google will too.
3. Identifying diseases
Not all applications of Machine Learning have to do with Google and its search engine. In recent years, Machine Learning has also become instrumental in identifying diseases and finding cures for them. A report from the Pharmaceutical Research and Manufacturers of America from 2015 stated that over 800 vaccines just to treat cancer (not including other diseases) were in trial at the time. So much data often proves a challenge as much as a benefit for the lab researchers, which is why they have to turn to Machine Learning specialists to disseminate it quicker.
4. Smart cars
According to auto execs, by 2025 we should see smart cars on the roads. For many, a smart car is just a car with a computer in it, but it is actually so much more. Thanks to Machine Learning, your car will be able to learn about you. Tell the car where you want to go and it will drive you there itself, while playing your favourite music, tuning the temperature inside to suit your preference and provide a real-time traffic report. Even self-repair if needed.
5. Make money laundering history
The biggest online banking system, PayPal and its users often have to deal with fraud and money laundering. To put an end to this, PayPal is now using Machine Learning and Deep Learning to figure out how a legitimate buyer or seller is and who is a swindler.
6. Financial trading
Want to be able to predict the stock? Every broker worth his or her salt will tell you this is almost impossible for a person to do. But what about machines? With ML algorithms trading on the stock market will soon seize to be the uncertainty that it has been since the first stock exchange opened.
Another use of Machine Learning that we are all looking forward to is in Radiology. Already, Google is partnering with the University College London Hospital on its DeepMind Health to develop ML algorithms that will be able to tell the difference between healthy and sick tissues.
8. Security screening
Unfortunately, the world is not a safe place anymore. Airports, music concerts, football stadiums and other places where a large number of people may gather has become a target for terrorists. This creates the need for extra screening and security. Unfortunately, this then leads to longer and slower queues and unhappy people. And plus, human screeners are liable to making mistakes, but Machine Learning can speed up the whole process and ensure everyone is safe and having fun at the event.
9. Predicting epidemic outbreaks
Machine Learning can also be used to predict an epidemic outbreak by collecting data from satellites, social media and web. There’s already a program, called ProMED-mail that reports on disease outbreaks in real time and more of these can certainly be invaluable in stopping epidemic outbreaks in their root, especially in third world countries.
How many times have you called a customer service, only to end up with more questions than you had at the start? Machine Learning, combined with Natural Language Processing (NLP) can actually be more helpful in providing you the information and the help you need to solve your problem. For example, ML can be more successful in determining what your experience with the product is and to offer you support based on that.