What are the uses of Unsupervised Machine Learning?
There are many uses of unsupervised machine learning. Computers are becoming more complex day by day with the help of modern technologies. These techniques enable computers to learn without any direct human supervision, leading to fewer mistakes as well as faster performance from the machine. The more uses that you can put your machine to, the better it becomes. This article will show you a few uses of unsupervised machine learning.
- Medical Transcription
- Language Translation & Communication
- Speech recognition
- Decision-making Capabilities
- Law Enforcement
- Currency Trading
The first application that we will see is for medical transcription. Transcription is the process where the audio output of a machine is translated into text. The main purpose of this is to create an electronic record of every patient consultation. If the machine can learn to interpret the different accents as well as medical terminologies, then it will create an accurate account of every event that is recorded. The resulting document will be much more comprehensive than the output of the computer alone.
Language Translation & Communication:
Another use of the training data that can be fed into the machine is for language translation. The system will be able to translate words from one language to another. The words will have to be placed within quotation marks. Once this is done, the resulting document will be accurate. The machine will learn to carry on conversations in both languages.
Another application is for speech recognition. Nowadays, computers are equipped with very good artificial intelligence. They can recognize individual symbols and syllables. By feeding the training data into the machine, you can train it to recognize common speech patterns and thus increase your business’s productivity.
When training unsupervised, your personal computer will also be able to handle all the analytics for you. You can set up various ways in which the machine can analyze the data and generate reports. It can tell you which promotional campaigns are working, which ones are not working and so on.
One other use of unsupervised learning is for decision making. Say for example you want to buy a new washing machine. You would probably do so either by trial-and-error or by looking at some reviews. If you were to do both of these methods, you would probably make a mistake. Of course, you could hire someone else to do this for you. However, it costs money. And in many cases, the machines used to do these tasks are not very accurate or reliable. But using unsupervised machine learning, you can let the machine decide based on the training data that it receives, which is more reliable than the other alternatives.
The biggest use of unsupervised machine learning is probably in the health care industry. With so much health care information now available on the internet, it is not long before your employees’ health is at stake. It is not possible for human doctors to review every piece of medical data that they receive in a timely fashion, and there are many things that can go wrong in a hospital without careful review by doctors. Unsupervised training data is the ideal way to avoid missing even the most important pieces of information that could really help your company improve.
Another common application is in law enforcement. Computer databases are being put together by law enforcement agencies all over the country, allowing them to quickly share intelligence about a person they are investigating. Without this information, it would be nearly impossible to track someone down, even if they were doing something wrong. Training data is the perfect way for these agencies to quickly and easily share information about criminal suspects, keeping the streets safe and the police officers themselves safe in the process.
Perhaps the most popular uses of unsupervised machine learning right now is in currency trading. Machines are now able to effectively trade currencies, keeping millions of traders around the world happy. This has huge implications for the money exchange business. If machines were used instead of people, there would be less risk involved, and the results would be faster. The results would be more accurate as well, meaning more people could turn a profit with less effort.
As you can see, there are countless ways that unsupervised training data is being put to good use today. They range from helping to combat terror threats in airports by allowing security staff to check if potential threats were real, to helping train students without human supervision in schools. No matter where you are or what you do, you could benefit from using this technology.