Linear Regression in Python – Real Python

This is just the beginning. Data science and machine learning are driving image recognition, autonomous vehicles development, decisions in the financial and energy sectors, advances in medicine, the rise of social networks, and more. Linear regression is an important part of this. Linear regression is one of the fundamental statistical and machine learning techniques. Whether you want to do statistics, machine learning, or scientific computing, there are good chances that you'll need it. It's advisable to learn it first and then proceed towards more complex methods. By the end of this article, you'll have learned: Free Bonus: Click here to get access to a free NumPy Resources Guide that points you to the best tutorials, videos, and books for improving your NumPy skills. Regression analysis is one of the most important fields in statistics and machine learning. There are many regression methods available. Linear regression is one of them. For example, you can observe several employees of some company and try to understand how their salaries depend on the features, such as experience, level of education, role, city they work in, and so on. This is a regression problem where data related to each employee represent one observation.