Recently I started a course on Applied Machine Learning by the University of Michigan on Coursera. The course covers some widely popular Machine Learning algorithms. I decided to write few brief articles regarding this topic, which are intended to help people new to this topic dive in the interesting world of Machine Learning. My last article covered the topic of K Nearest Neighbours (KNN) classification. You can take a look how to use KNN to classify cars into vehicle classes according to their engine size, cylinder count, fuel consumption and CO2 output. Today we go further, and tackle Linear Regression, another extremely popular and wide used technique.

Structure of the article:

• Introduction
• Dataset loading and description
• Data analysis
• Model training and evaluation
• BONUS: Polynomial Regression
• Conclusion

Enjoy the reading! 🙂

#machine-learning #data-science #linear-regression #python-programming