Machine Learning to Face the World of Data Science


Machine Learning itself is an artificial intelligence that focuses on developing a system that is capable of “self-learning”. With machine learning, you can find out the trends of a business. Machine Learning is part of the science of artificial intelligence Artificial intelligence that combines statistics and programming, which gives computers the ability to learn things without having to be programmed explicitly. Of course, Machine Learning has a big impact on the future. For example, currently an autonomous car is being developed, which can be a solution to minimize driver accidents in the future through machine learning computer vision.

The supervised learning type is used to solve a case. Usually the data owned has a target that you want to predict for the future. For example, targets to predict age or gender. Its function is to predict, to classify. So there is input and there is a target variable that you want to predict. Supervised Learning is a machine learning algorithm that can apply information that already exists in the data by giving certain labels to the previous data.

In contrast to supervised learning, in the type of unsupervised learning a data practitioner does not always have to have a special label to predict. Based on the mathematical model, the algorithm in unsupervised learning does not have a target of a variable. Unsupervised Learning is a machine learning algorithm that does not require training data and certain labels beforehand. This algorithm finds hidden patterns or intrinsic structures in the data itself.

In the telecommunications industry Machine Learning plays an important role, usually machine learning is used from data generated from available services. Sometimes also from external data such as social media, market places, and many more. The goal is none other than to optimize our services. For example, we use machine learning to personalize customers with the right treatment, to stay loyal to our products.

Leave a Reply

Your email address will not be published.