The role of machine learning begins primarily with data mining and analysis. The results of this analysis can form the basis of a report or a machine learning model, but it all starts with data. In this article, I will explain to you what is the role of Machine Learning.
Machine learning is a subset of data science that deals with predictive modelling. In other words, using data to create models capable of predicting unknown values.
Role Of Machine Learning
Machine Learning works by identifying the relationships between the data values that describe the characteristics of its features and the labels we want to predict and encapsulating these relationships in a model through a learning process.
Usually, a machine learning task is designed to establish information about a particular scenario or to test a hypothesis. For example, suppose a college professor collects data from machine learning students, including the number of courses taken, hours spent studying, and final grade on the end of term exam.
The professor could then take a sample of the data and analyze it to determine if there is a relationship between the amount of study a student undertakes and the final grade they obtain.
They can use the data to test the hypothesis that only students who study for a minimum number of hours can expect to achieve a passing grade or even prepare the data to train a machine learning model that predicts the performance grade of a student according to his/her study habits.
So, in machine learning, we have to train algorithms to find patterns and relationships between massive amounts of data to make decisions and predictions based on new data. The better the algorithm performs, the more accurate decisions and predictions will become as it processes more data. This is what the role of Machine Learning is.
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