<html><head></head><body><p>In the previous lessons from the series of lessons on Machine Learning (ML) in robotics, we learned how to set up our project environment and how to code in an IDE using the Python language.</p><p>This lesson is about linear regression in machine learning (ML). We will understand the basic theory behind linear regression, and we will get ready to implement linear regression in a real-life situation using Python in our next lesson. We will also use an algorithm called Gradient Descent which is an optimization algorithm to find the minimum of a function.</p><div><figure class="image"><img src="https://minio.news.mecharithm.com:443/mecharithm/Linear_Regression_for_Machine_Learning_Gradient_Descent_Algorithm_0b96b2ab12.png" alt="Linear Regression for Machine Learning_Gradient Descent Algorithm" width="501px"><figcaption>Machine learning begins with the most straightforward and basic concept, linear regression in machine learning.</figcaption></figure></div><p></p><p>Watch the video version of the 4th lesson:</p><figure class="media"><span></span><iframe src="https://www.youtube.com/embed/MkEYKHJCjIQ?autoplay=0" allow="autoplay" allowfullscreen="" title="video"></iframe></figure><p></p></body></html>

Machine Learning(ML)course

In the previous lessons from the series of lessons on Machine Learning (ML) in robotics, we learned how to set up our project environment and how to code in an IDE using the Python language. This lesson is about linear regression in machine learning (ML). We will understand the basic theory behind linear regression, and […]
