One of the most important characteristics of a human being is his intelligence. Humans have the ability to learn almost everything. Of course, some animals have this ability to some extent. But objects cannot learn or speak and communicate. So when you give your phone commands to do, or when you talk to a robot, what are you communicating with? Is it other than that you are actually talking to an object?
Machines can also learn and become intelligent. Machines can also recognize humans. Machines can do things they were not programmed to do. Machines can improve themselves. Yes! With Machine Learning, things may become intelligent.
There is no turning back from the developments that happen every day in the field of machine learning. Machine learning finds new applications every day and becomes more industrial and commercial. In 2022, not only the previous applications of machine learning have been improved, but machine learning has been used in new areas. In this content, I intend to introduce you to 5 of the most interesting applications of machine learning in 2022.
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The most interesting applications of machine learning in 2022
Before introducing the most interesting applications, it is better to say very briefly what machine learning means. Of course, the introduction also mentioned what machine learning is. We think that in order for machines to do things, they need to be given commands. But not all cars are like that. Ever since the science of artificial intelligence was born, humans have been able to train machines using algorithms. Machine learning and deep learning are sub-branches of artificial intelligence. With machine learning, there is no need to tell the machines everything. They can do things they weren’t designed to do by finding patterns and relationships in raw data.
“Machine learning is an umbrella term for a set of techniques and tools that help computers learn and adapt on their own.”
1. Applications of machine learning in social networks
Machine learning is used in various fields. It can be claimed that one of the most widely used areas is the use of machine learning by various social networks to recognize their users. Be sure that the use of machine learning to improve our interaction with social networks is increasing every day.
You may not have noticed that every time you open Facebook or Instagram, you are actually helping an algorithm learn. Yes! Every time you like a post or even open and view a post, you are telling the machine learning algorithms of Facebook or other social networks something new about your interests and yourself. Based on the information that the user provides to the algorithms, someone or a post in these networks is suggested to him.
2. Applications of machine learning in analyzing people’s emotions
Analyzing people’s feelings (speaker or writer) is one of the latest applications of machine learning. Imagine you sent an email to your boss and asked him to agree to your leave for a few days. He will review and reject your request. You send a second email thanking him ostensibly for considering your request and saying you didn’t need the leave at all! But inside you are very angry and sad and you feel that you can no longer work in this company. An algorithm can detect how you really felt when you wrote that email! Think what this sentiment analysis algorithm can do!
No writer or speaker can hide their true feelings anymore. This application of machine learning is very important for businesses and to know the real feeling of users and customers towards their products. Also, with this analyzer, you can understand that the person who wrote a recommendation or introduction or review of a product on a site, really wrote the truth or hid his true feelings.
3. Applications of machine learning in environmental protection
In my opinion, this is the most interesting and interesting application of machine learning. Humans can help the environment and preserve endangered species with the help of machine learning algorithms and the predictive power of these algorithms. This is great and very promising. Of course, it will take some time to develop this application to control environmental crises and climate change. But the important thing is that scientists took this path.
To give a more specific example of this application, I would say that machine learning algorithms can predict population changes in endangered marine mammal species. By identifying these species in different regions of the world and monitoring their remaining population and monitoring their behavior, scientists try to find solutions to increase the population of these species.
- Applications of machine learning in improving the quality of healthcare services
Among other very important and useful applications of machine learning that positively affects the lives of many people are the various applications that machine learning has found in different parts of the healthcare system. Machine learning algorithms are used to improve management and service quality in these sectors. For example, machine learning algorithms can predict the average time patients will have to wait in the emergency department. This application is especially helpful during crises and accidents when hospitals face a large number of emergency patients and saves human lives. Another example is the application of machine learning to predict the progress of diseases and the effectiveness of certain treatments.
5. Applications of machine learning in banking
With machine learning, the provision of banking services and the interaction of customers with banks can be made better and safer. The most important application of machine learning algorithms in banking is to prevent hacker attacks and fraud, as well as to protect account information. Algorithms can identify fake sites and prevent financial transactions from those sites.
With machine learning, bank employees no longer need to do some repetitive tasks. With the help of machine learning algorithms, many banking processes were automated, which is called Process Automation. In the not too distant future, more and more administrative processes and paperwork of banking systems around the world will be automated. This automation has other important advantages, which is the reduction of human errors in work, as well as the quick detection of inconsistencies and suspicious transactions by means of algorithms.