In the midst of the rapid development of artificial intelligence (AI) technology today. Not many people know that artificial intelligence consists of several branches, one of which is machine learning. This machine learning (ML) technology is one of the branches of AI that is very interesting, why? Because machine learning is a machine that can learn like humans. Learn more about it on computer vision datasets.
Back to artificial intelligence. Artificial intelligence in its application is broadly divided into seven branches, namely machine learning, natural language processing, expert systems, vision, speech, planning and robotics. The branch of artificial intelligence is intended to narrow the scope when developing or learning AI, because basically artificial intelligence has a very broad scope.
Machine learning (ML) technology is a machine that was developed to be able to learn by itself without direction from the user. Machine learning is developed based on other disciplines such as statistics, mathematics and data mining so that machines can learn by analyzing data without needing to be reprogrammed or ordered.
In this case machine learning has the ability to obtain existing data with its own commands. ML can also study the existing data and the data it obtains so that it can perform certain tasks. The tasks that can be done by ML are also very diverse, depending on what he learns.
The term machine learning was first put forward by several mathematical scientists such as Adrien Marie Legendre, Thomas Bayes and Andrey Markov in the 1920s by stating the basics of machine learning and its concepts. Since then ML has developed a lot. One example of a well-known application of ML is Deep Blue, which was created by IBM in 1996. Deep Blue is a machine learning developed to be able to learn and play chess. Deep Blue has also been tested by playing chess against professional chess champions and Deep Blue has won the chess match.
The role of machine learning helps humans in many fields. Even today, you can easily find the application of ML in everyday life. For example, when you use the face unlock feature to unlock your smartphone, or when you browse the internet or social media, you will often be presented with some advertisements. The ads that appear are also the result of ML processing which will provide advertisements according to your personality.