The Technological Revolution Of Machine Learning
What Is Machine Learning?
To understand the importance of Machine Learning, the first thing is to know what we mean. Machine Learning is about what the word itself indicates, endowing a machine with the ability to learn, just as we humans do. It is true that hearing the statement that a machine can learn to manage various tasks as if it were a human being can cause a bit of fear, but let’s hope that it is only beneficial. There is no ‘reveal of the machines’ as speculated many times.
Machine Learning Applications
If the power to equip a machine with learning is so important because it is not used, you will think. Even if you don’t realize it, Machine Learning is used in many fields or for many tasks that you had never considered how they were carried out. For example, we have the case of voice assistants. When you use your voice to give a command to the device, what it does is translate those words into text. Once he understands what you mean, he does an internet search or even responds to you. This can only be done if the machine has been learning, for example, what ‘Play a YouTube video’ or ‘Tell me the time’ means.
And it is not only present in the fields of entertainment. It can also be used to create a 3D model of various medical tests and, with increasing accuracy, to be able to detect and prevent tumors, for example. Suppose the machines can recognize tumors in a still very reduced state. In that case, it may be possible to eradicate them from the body without further problems, which detecting them, thanks to the fact that the machines have learned to do so, can save many lives.
How Does It Work
What is done is to provide the machine with certain information as a base. Once that is done, the next thing is to enter data so that it can develop a task and learn from mistakes. That is to say, it acts as the human mind. The main idea would be the following: Introduced to the machine with the label that it is a cat, then different photographs such as number 2 are passed to it to learn what it is a cat. When he has enough information, you can send him a picture of any cat, and he recognizes it. On the other hand, if you send him one of the dogs, he has to detect that it is not a cat.
It is a fundamental way of explaining how it works, but enough to understand it. Things get more complex in much more complicated tasks, such as a car driving autonomously, but the basis is the same: obtain information and learn from it and its mistakes. To conclude, I have to say that even though a significant advance has been made in Machine Learning, there is still a long way to go and who knows, it may be that in the future, many the important diseases will be eradicated or the driver’s license it is only used in circuits since cars will have the ability to circulate autonomously. It is a future that may terrify some, but it is also true that it will be exciting to know to what extent life can be improved.