Multiple Linear Regression with Gradient Descent from Scratch

In this episode of the Machine Learning fundamentals series, I show you in more detail how linear regression models work, how they are trained including the Normal Equation and Gradient Descent, and finally how to code all of this from scratch to get a deeper understanding. #machinelearning #ml Colab Notebooks: https://drive.google.com/drive/folders/16fu-B4-Iz2GZdcSe0mIYJ739tk1gNCWw?usp=sharing Join the Community! - https://rebrand.ly/discordlink Want to Support the Channel? - Become a Member: https://www.youtube.com/KodySimpson/join - https://buymeacoffee.com/kodysimpson My Socials: Github: https://github.com/KodySimpson Instagram: https://www.instagram.com/kody_a_simpson/ Twitter: https://twitter.com/kodysimp Blog: https://simpson.hashnode.dev/ Timestamps: 0:00:00 - How Linear Regression Works 0:26:35 - Implementing the Normal Equation 0:33:57 - Gradient Descent 0:53:03 - Vectorized Gradient Descent More Videos coming soon. Leave a comment for any future video suggestions.