Learn in 1 Hour: Linear Regression in Machine Learning

Anastasia Khramushina

We are almost at the finish line of the Hour of Code. You are doing great! If you haven’t read our previous “Learn in 1 Hour” posts, check out our lineup in Hour of Code at JetBrains Academy. The next one hour of learning we dedicate to linear regression, which is an essential topic for those who are interested in machine learning!

Machine learning as a part of artificial intelligence is a field of knowledge whose goal is to create algorithms that can learn from past experiences and transfer this knowledge to new, unseen cases. Machine learning is developing at an incredible pace and becoming more and more prevalent in our daily lives. Algorithms allow map apps to build the fastest route to a selected destination, self-driving cars to operate, and social media to build news feeds according to our interests.

One of the main subcategories in machine learning is called supervised learning, where the goal is to learn to predict some target attributes from the values of other example attributes, often called features. If the target attribute of the model is numerical, the problem is referred to as regression. An example of a regression problem would be predicting the yearly income of a person based on their education, occupation, background, and other points, or predicting real-estate prices based on the location and size of the property.

One of the simplest regression models is called linear regression. As the name suggests, it models the value of the target variable as a linear function of the inputs.

With 6 educational topics and just 1 hour to spare, you will get a solid introduction to linear regression at JetBrains Academy. Not only will you learn the theory, but you will also solve quizzes and complete coding tasks to practice your new skills:

🕐 Simple linear regression
🕐 Multiple linear regression
🕐 Regularized regression
🕐 Linear regression in sklearn
🕐 Regularized regression in sklearn

If you are already familiar with linear regression or would like to practice with something more challenging, we invite you to take a look at our Python project: Linear Regression from Scratch.

This project will guide you through all the fundamentals of linear regression and help you build your own linear regression model. You will also learn to use the Numpy library, learn about fit, prediction, and the score method, and compare your model against the Scikit-Learn Linear Regression algorithm.

Explore Linear Regression

We are so thrilled to read your stories about your one-hour experience with JetBrains Academy! If you haven’t joined the #HourOfCode celebration yet, don’t miss your chance — there are only 2 days left. Share a story about something interesting, challenging, or fun you’ve done at JetBrains Academy in 1 hour and get a chance to win a 25% discount on your personal subscription at JetBrains Academy. Learn more about the rules in the Hour of Code at JetBrains Academy blog post.

Happy Hour of Code!
Your JetBrains Academy team

Subscribe to JetBrains Academy updates

Subscribe form

By submitting this form, I agree to the JetBrains Privacy Policy Notification icon

By submitting this form, I agree that JetBrains s.r.o. ("JetBrains") may use my name, email address, and location data to send me newsletters, including commercial communications, and to process my personal data for this purpose. I agree that JetBrains may process said data using third-party services for this purpose in accordance with the JetBrains Privacy Policy. I understand that I can revoke this consent at any time in my profile. In addition, an unsubscribe link is included in each email.

Submit

Thanks, we've got you!