One of the terms that has recently gained a lot of popularity is Machine Learning (ML). But what is this concept and how does it apply in the industry?
To begin, we will define ML as a type of artificial intelligence in which machines are programmed to adapt their algorithm as they receive information, turning them into computers with machine learning capabilities. The data is reviewed to find patterns and thus the system is able to predict future behavior. This technology reduces human intervention to the minimum possible and allows a large number of operations to be automated.
This discipline has a wide range of applications, including search engines, credit card fraud detection, medical diagnostics, speech and written language recognition, stock market analysis, DNA sequence classification, and robotics, among others.
ML can also be found in the digital realm. One example is Facebook’s news feed, which displays personalized information for each member of the social network. It works like this: if a person frequently stops scrolling to read, comment on, or like a particular friend’s posts, the news feed will start to display more activity from that friend. In this case, the software simply uses statistical analysis and predictive analytics to identify patterns in the user’s data and thereby populate the news feed. If the member no longer interacts with the friend’s activities (reading, liking, or commenting), those new details will be included in the data set and the news feed will be adjusted so that it no longer displays the friend’s activities.
Another use of Machine Learning is in the field of cybersecurity through biometrics. With the rise of the Internet, banking transactions and online shopping, the need for security has become essential. For this reason, technology has expanded the capacity for biometric identification, including hand geometry, iris scanning and facial recognition. The union of ML with these recognition systems has been a great step for technological evolution and for this reason it is recognized as the future of security.
