Adrià Moya Morera
7 de enero de 2023
Have you ever wondered how computers can "learn" things on their own and improve their performance as they gain more experience? Well, that's what machine learning does!
What is machine learning? It is a branch of computer science that is responsible for developing algorithms that can learn on their own and improve their performance as they gain more experience. And how do they do it? Through techniques such as supervised learning, unsupervised learning and reinforcement learning.
Unsupervised, supervised and reinforcement learning and their differences.
Supervised learning is when algorithms are provided with labeled examples, that is, they include both the data and the correct answer. Thus, the algorithm can learn to make decisions or make predictions about similar data in the future.
Unsupervised learning, on the other hand, is when algorithms are provided with unlabeled data, that is, without the correct answer. In this case, the algorithm has to discover for itself the relationships and patterns present in the data.
And finally, reinforcement learning is when the algorithm is provided with a specific goal and is rewarded or punished for making right or wrong decisions. Through this process of trial and error, the computer can learn how to make decisions that maximize reward.
How can we apply it in decision-making on our businesses?
And what are the capabilities of machine learning in decision making? Thanks to its algorithms, computers can make decisions and make predictions more accurately and quickly than humans. And that's just the beginning, as machine learning is a valuable tool in a wide variety of applications, such as data analysis, pattern recognition, and process automation.
So that's what machine learning is and how it works! Isn't that fascinating? I hope you enjoyed reading this as much as I enjoyed writing it. See you next time!
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