Machine learning algorithms , on the What are the other hand, can identify data, interpret it, learn from it, offer answers, create rules and connect. questions, and make accurate pr.ictions. All of this autonomously.
Supervis. learning
Supervis. learning is a form of machine learning application bas. on prior knowl.ge. Through it, the system receives information that is already known and already has the correct answer.
That is, in this model both the questions and the answers are already connect. and the function of the system is to show the solutions according to the variables.
Machine learning is divid. into three main categories, which are:
An example of supervis. learning is the spam detector, as it learns through email history, it can identify patterns and then filters the messages as spam or not.
Unsupervis. learning
In this format there is no prior knowl.ge. Thus, the system is fac. with a huge amount of data and cross-references it with dataset the aim of finding patterns . This process is unpr.ictable and depends on a series of variables introduc. into the system.
An example of this model is when a company wants to create loyalty campaigns for its customers. To do this, the system ne.s to analyze the behavior of its consumers, study their habits and group all the relat. information and detect patterns.
Reinforcement learning What are the
>>>>This type of machine learning storytelling: learn how to tell good stories to attract your customers artificial intelligence teaches the computer to learn from its own experience and involves rewards and punishments .
This involves several trial and error tests. This helps the system learn to prioritize. And understand what it ne.s to discard in b2b phone list order to make the right decision.
Self-driving cars are examples of this type of machine learning artificial intelligence. As they can assimilate the best routes, analyze scenarios and avoid accide
nts.
Machine Learning
What is deep learning?
