Learn what Machine Learning means and learn about the different ways it is applied in the main companies in the market.
The most varied technological resources are part of our routine without realizing it. And that’s exactly what happens with Machine Learning.
Despite being a science discovered some time ago, its use for the development of technology is recent. In addition, it is present in our daily lives even if we don’t know what it is. Therefore, learn what Machine Learning is and where it can be applied in your business.
What Is Machine Learning
In free translation, Machine Learning is Machine Learning. That is, it is the ability of computers to learn on their own through data analysis.
In this way, human interference is practically null, only necessary to create a pattern in the first moment. Soon after, the machines learn according to their own experience.
Consequently, algorithms are responsible for finding behavior patterns and delivering content relevant to the analyzed profile.
Practical Examples Of Machine Learning
Now that you know what Machine Learning is, let’s introduce you to how leading companies use this tool.
Transport applications initially use the tool to optimize its use. Among others is whether to calculate smaller routes with less traffic, fares, and waiting time for the driver.
But now, they also use it to guarantee greater security for users. As such, algorithms identify risks through real-time data analysis.
If you use a streaming platform, you will likely receive notifications recommending movies and series from your favorite genres.
This is only possible thanks to the use of Machine Learning. That is, based on what you watch and your browsing behavior; it recognizes which ones you will most likely like.
Webmail services, on the other hand, use technology to separate incoming emails into categories. For example, spam, commercials, and updates, among others.
In this case, you need to consider the sender (if they have contacted you before, not only by email but in applications that are logged in with that address), location and specific words.
Online Sales Websites
It can also be used to increase sales and attract new customers. Therefore, it is possible to recognize, for example, customers who abandon the cart to get in touch and remind them to finalize the purchase.
In addition to the items above, using Machine Learning enables greater recognition and prevention of fraud and cybercrime as it recognizes breaches in established standards.
Difference Between Machine Learning And AI
You might think that Machine Learning could be the same as Artificial Intelligence. But not exactly!
AI is a broad field encompassing many areas and techniques to create intelligent systems with human abilities.
Thus, Machine Learning is a strand/subcategory of AI that aims to train machines to learn behaviors from data. That is, no human interference is required. This is because the system itself, through analyses, learns to execute the programmed tasks.
The more data the system has access to, the more assertive the results will be. The database information must also be automated to avoid mismatch errors.
What Are The Advantages Of Using This System?
Now that you know this technology, it’s time to know the advantages!
We gave the example of Netflix, which uses Machine Learning to suggest movies and series according to each profile.
That is, according to the user, it is possible to customize the suggestions assertively. And consequently, it increases the probability that that movie will be watched since the recommendation is made for a user who likes that particular genre.
As the algorithms analyze the data and find patterns in that information, it’s easy to spot potential anomalies.
Therefore, Machine Learning is one of the most complete tools to identify cyber crimes.
Machine Learning cuts down on internal processes. A human doesn’t have to analyze data by data since the system does everything automatically.
This way, it is possible to identify problems quickly based on concrete information without any error occurring in the middle of the process.
As we mentioned in the previous topic, with Machine Learning, the chances of making a mistake in data analysis are practically zero.
Therefore, it is possible to analyze a much larger amount of data. Also, quickly. Consequently, it influences the speed with which the company’s actions are taken since you don’t have to wait long to get the information.