In the previous lesson, we learned about linear regression in machine learning (ML). We understood the basic theory behind linear regression, and we got ready to implement linear regression in a real-life situation using Python in this lesson. We also used an algorithm called Gradient Descent which is an optimization algorithm to find the minimum of a function.
Please read the following lesson first if you are not familiar with linear regression in machine learning:
This lesson is about the linear regression machine learning example. We will use linear regression to solve a stereo vision depth estimation problem for an Autonomous underwater vehicle (AUV). We will also implement vectorization using Python.
You can download the Python code for this problem (lesson5-pycode) at the link below:
https://github.com/mecharithm/ML-first-steps-course.git
Watch the video version of the 5th lesson:
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