Linear Regression for Machine Learning: a Case Study | Stereo Vision Depth Estimation | Lesson 5
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.
In this lesson, 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.
Download the Python code at the link below (lesson5-pycode):
https://github.com/madibabaiasl/ML-fi...
🌟 Contents 🌟
💎 (00:00) Introduction
💎 (02:09) Vectorization Concept
💎 (04:04) Linear Regression Case Study (stereo vision depth estimation problem for an AUV)
💎 (52:35) Summary
Note that for your convenience, all lessons are organized into a playlist.
Thanks for watching! We'd love to have you as a part of the Mecharithm family:
https://linktr.ee/mecharithm
👉 Subscribe to our channel for more learning and news in Robotics and Mechatronics.
💲 If you enjoyed this video, please consider contributing to help us with our mission of making Robotics and Mechatronics available for everyone. We sincerely thank you for your generous contribution (you can do this by the Thanks button under the video).
©️ Tutorials and learning material are proprietary to Mecharithm, but sampling is permitted with proper attribution to the main source.
#linearregression #machinelearning #machinelearningbasics #machinelearningfullcourse #ml #robotics #mechatronics #roboticslearning #stereovision #depthestimation
