What Is Machine Learning? Different Fields Of Application For Machine Learning

Machine Learning is not only becoming important for researchers or IT companies such as Google or Microsoft, but it also plays a very important role in online marketing, which is changing with the advancement of AI. 

Machine Learning is the science of getting computers to act without being explicitly programmed. Its most basic application is the practice of using algorithms to process data, learn from it, and then be able to make a prediction or suggestion about something. These are models that are capable of learning and adapting independently to the natural evolution of the data.

Different Fields Of Application For Machine Learning

Marketing is not the only area in which the application of machine learning grows progressively, but it also has a presence in many other fields: it contributes to the progress of science, supports the advancement of technology, facilitates the day to day thanks to electronic devices, etc.

These are just some examples within the wide variety of fields of action of machine learning, which makes us suppose that in the not too distant future this type of intelligent system will be present in all aspects of our lives.

Science

In the field of science, machine learning is of equal or greater importance than in the field of marketing, since the intelligent processing of big data greatly facilitates the work of researchers. 

For example, particle physics takes a larger volume of measured values, processes them, and thus determines the deviations. But it is also very useful in medicine since today doctors use artificial intelligence to diagnose and apply treatments, in addition to using machine learning to predict diabetes or heart attacks.

Robotics

The omnipresence of robots is especially important in factories. These are necessary for mass production since they allow to automate different work processes, but in general, they have little relationship with self-learning systems, since they are programmed to carry out a specific activity in a repetitive way and without variations. 

However, if autonomous learning were introduced into these processes, machines could learn to master other tasks. But robots that integrate intelligent systems can also be useful in many other fields, ranging from the space race to the home.

Traffic

One of the great challenges of machine learning is autonomous driving. Making cars capable of driving themselves and without causing accidents outside the test circuits can be made a reality thanks to these intelligent systems.

 As it is not possible to program all situations, it is important to equip autonomous cars with Machine Learning systems, but autonomous driving is not the only field in which these systems have made their mark, given that intelligent algorithms in the form of neural networks They can analyze traffic and develop effective systems that, for example, regulate smart traffic lights, thus alleviating the flow of traffic and preventing the formation of congestion.

Internet

On the Internet, intelligent learning constitutes a very important piece. The spam filter has already been named above. With progressive learning, this program filters unwanted messages more and more accurately and makes spam disappear from the inbox.

 The same is the case with intelligent programs that protect computer systems from viruses and malware more and more effectively. The search algorithms of search engines, especially RankBrain of Google, are also self – learning systems. Even when the algorithm doesn’t know how to deal with a user’s search because it’s the first time someone’s searching, it can deduce what your query might be about.

Personal Assistants

In the private sphere of the home itself, the importance of these increasingly intelligent computer systems is increasing, transforming traditional homes into smart homes. Moley Robotics has developed, for example, a smart kitchen that with its mechanical arms can prepare meals.

 Also, personal assistants such as Google Home and Amazon Echo, from which it is possible to manage one’s own home, use machine learning to understand users in the best possible way. Also, many people carry assistants with them, since Siri, Cortana, and the Google assistant allow users to ask questions or send orders to the smartphone through voice commands.

Games

From the beginning of the studies around artificial intelligence, the researchers’ attention was drawn to the ability of these programs to participate in games, which has been demonstrated in chess, checkers, or Go, a game from China and probably the Most complex game board in the world, facing machine learning systems and human beings.

In the case of video games, developers turn to these machines to make their games more interesting. In addition, game designers can install this autonomous learning to create the most balanced game possible between the computer and the real players