Have you ever noticed that when you watch something on Netflix it acts like a friend who knows your tastes and always recommends you cool movies? Or when you do a Google search, are the first results almost always what you were looking for? Or even that Siri or Alexa can understand you and help resolve your demands? Well, all of this is possible thanks to machine learning.
All these tools make use of this technique to be able to understand your speech, provide more specific answers to your searches or even predict your tastes and desires based on your purchases or programs you usually watch.
In constant evolution, machine learning is a subfield of artificial intelligence that allows the computer to learn by itself using data or past experiences through the use of a wide variety of algorithms that allow systems to identify patterns and make decisions.
As the algorithms process the training data, more accurate representations are created based on these examples and as an end result of this learning process we have a model that can be used to make predictions based on new inputs.
Machine learning is a very exciting area with its ability to deal with massive amounts of data and recognize patterns that might otherwise be impossible for humans to detect.
I would venture to say that machine learning is the heart of AI as it has proven essential for many of the practical applications such as speech recognition, image recognition, fraud detection and others. Even big market leaders like Facebook and Uber use ML as a core part of their operations.
In addition, according to Statista (a German research and data analysis company), the total amount of data expected to be created and consumed globally in 2023 is 120 zettabytes and with this exponential increase in the volume of information, machine learning passes to be fundamental for decision-making in companies and can be considered a determining factor for competitive advantage in the market.
As you explore the fascinating world of machine learning, you discover that there are many applications and impacts across industries. Now, it’s time to deepen your understanding of the different types of machine learning. Find out how each of them works, their differences and practical examples in my article: “What is supervised, unsupervised and reinforcement machine learning?”. Thus, you will be even more qualified to understand and explore the possibilities of this incredible technology.
