How Does Artificial Intelligence Learn?

Artificial intelligence is a term coined by John McCarthy in 1958. This refers to the development of various methods, as well as algorithms, which they allow computers to behave in an intelligent way. In fact, it can be said that artificial intelligence is to make human knowledge computational by symbolic or connectionist procedures, that is, Imitate human behavior. Importantly, computational thinking refers to the way to solve problems by applying pattern detection, abstraction and logical reasoning.

Thanks to great technological advances, artificial intelligence has allowed great progress in various areas such as finance, education, agriculture, health, commercial, climate, logistics; also, mobile applications, bots, virtual assistants, promoting Application of Big Data in all business fields. Making preparation indispensable through masters and courses To, thus dominate the spaces of the Date Science.

What is needed to program artificial intelligence?

There are a number of knowledge and skills that must be considered when programming artificial intelligence. For example:

Mastering programming languages, which are a set of codes and symbols such as, Java, which is considered to be multipurpose and ideal for developers and is the most used in the world. On the other hand, it is, the Python language, is one of the most requested in Master Data Science Madrid, because, allows you to design applications in artificial intelligence.

In the same way, it is PHP, which offers excellent tools to programmers; another is C++, is an extended version of the C language; and, Ruby, a simple programming language, easy to read and understand.

Also, develop skills in advanced mathematics; since it depends on it that you can correctly handle programming languages, variables, constants and other functions of artificial intelligence.

In addition, knowledge is necessary in various technological fields, such as Big Data. In addition to this, design, languages, engineering, spreadsheets, among others. You can specialize in Master Data Science for Professionals, Master Data Engineer, Master in Artificial Intelligence among others masters and courses.

Types of Machine Learning

The”Machine learning” or machine learning, is considered to be one of the disciplines in the field of artificial intelligence; which, through algorithms, allows computers to recognize the patterns that arrive in massive data, and thus be able to make predictions; thus allowing the computer to perform specific tasks. This The technique of learning automatically is indispensable in Big Data.

There are several types of machine learning, described below:

• Supervised: It refers to a process of producing knowledge, which is carried out with a set of data, which are labeled; this allows the results of the operation to be previously known. In addition, this model feeds a large group of results, which allow predictions and decisions to be made about the behavior of the new data. In fact, this model is incorporated into several applications that serve as spam detection filters in emails, as well as in captchas, voice recognition, among others.
• Unsupervised: This learning model does not have prior knowledge of its structure. That is, you are faced with a disordered, unlabeled data set, and without output variables. The function of unsupervised learning is to obtain information that is key by exploring the structure of data that has not been previously labeled. There are two categories in this machine learning, clustering and dimensional reduction. The first refers to the exploration that allows data analysis in order to organize information into groups with similar characteristics; this technique is the most popular in marketing strategies. The second is responsible for those data that are more complex and have the greatest demand and processing capacity; in order to identify the correlations between the characteristics of the data group to reduce data redundancies and analysis time, thus obtaining valuable information.
• Semi-supervised: The combination of supervised and unsupervised learning is used. This makes it possible to produce important information about those available data using both labeled and unlabeled data.
• By reinforcement: Also known as Deep Learning, whose main objective is the construction of models with high decision-making performance taking into consideration past experience; that is, knowledge is obtained from one's own experience. The process consists of trial and error, and is reinforced with a reward when a correct decision is made; this allows for adjustment in behavior to take action in the future.

Through the artificial intelligence machine learning models can be built to identify customer behavior, markets, marketing, among others; and thus develop the best strategies.

What are the types of AI?

1. Reactive machines: As the name suggests, their decision-making is based on what they see in the present, they don't keep memories of their past actions. An example of this type of artificial intelligence is Deep Blue, the famous IBM supercomputer that was able to defeat chess grandmaster Garry Kasparov. Reactive machines are created for specific functions based on their actions on what they see, not on memories that allow them to learn in relation to them.
2. Limited memory: These types of machines are able to store past data, albeit temporarily. This allows them to make decisions by looking to the past to create behavioral patterns. Its disadvantage is the limited time in which you can wait for such information.
3. Theory of Mind: They are machines capable of identifying the behavior of everything that surrounds them, such as people, animals and even objects. This concerns the thoughts, sensations and emotions that affect actions in social interaction.
4. Self-awareness: Many believe that this is the last step in artificial intelligence. These would be machines capable of self-representation, self-awareness and predicting the feelings of others.

Artificial intelligence is no longer science fiction, it is immersed in the strategies of each of the fields of action that surround us, and they are part of the evolution of humanity.