Learn how to implement a Linear Regression model in Python using just math and NumPy (no machine learning libraries like Scikit-Learn). I’ll start by explaining the core math concepts behind linear regression, including the cost function and gradient descent, and then walk through how to turn those equations into code.
This is part of my Machine Learning From Scratch series, where I'll be building ML algorithms from the ground up, step-by-step to truly understand how they work under the hood.
📺 Watch the Playlist Here: https://www.youtube.com/playlist?list=PLh6JMkwECi5HXVJ58ue58jJvL599NFYja
📊 Kaggle Dataset: https://www.kaggle.com/datasets/krishnaraj30/salary-prediction-data-simple-linear-regression
💻 Full Code on GitHub: https://github.com/harryconnor/Machine-Learning-From-Scratch
TIMESTAMPS:
00:00 - Introduction
00:22 - PART 1: The Math
04:10 - PART 2: Coding it up
#machinelearning #python
