Machine learning applications, the algorithms are trained to find patterns in big data. The goal is to make a prediction or decision based on existing data. The better the algorithm made, the higher the accuracy value, so the predictions or decisions to be taken are getting better. Machine learning has begun to be used in various fields, with this algorithm human work becomes much easier. One of the fields that are starting to take advantage of this technology is agriculture. The use of machine learning for computer vision aims to increase production and reduce risk in the field.

Supervised learning is one of the algorithm methods used in machine learning. Have you ever heard of supervised learning or machine learning? The field of AI (Artificial Intelligence) technology continues to grow rapidly, especially in machine learning. So, what is machine learning?

Machine learning is an algorithm that is inserted into the machine so that it can do learning independently, without any help from humans. Machine learning has the ability to explore data, study data, and generate output into several actions based on the data obtained. The concept of this machine learning algorithm has been put forward since the 1920s by mathematical scientists, namely Thomas Bayer, Adrien Marie Legendre, and Andrey Markov. Those who propose and develop machine learning models.

In today’s human life, the presence of machine learning certainly has enormous benefits. Machine learning can learn what users need, what interests them, and so on. Then, how can this machine learning do self-learning? This is where we will enter into the opening discussion of supervised learning or directed learning.

Machine learning has 2 basic independent learning techniques, namely supervised learning and unsupervised learning. The two basic learning techniques have different ways of learning so their application is based on the learning needs of machine learning itself.

For example, everyone must have a different way of learning. There are people who can understand learning topics just by reading, there are people who have to listen to learning materials in an auditory form, and there are also people who have to rewrite them. The difference in the way each person learns also applies to machine learning. So, supervised learning and unsupervised learning are 2 different ways of learning in machine learning.