Скачать или смотреть Linear Regression From Scratch in NumPy | ML Foundation (Day - 1)

This video is Day 1 of Week 1 (Machine Learning Recap) in a structured AI Engineer learning path.
In this lesson, we build Linear Regression completely from scratch using NumPy, without using scikit-learn or any high-level machine learning libraries.

The goal is not to “use” machine learning, but to understand how it actually works.

What this video covers:
What supervised learning really means
How linear regression models a relationship between input and output
Why feature scaling (standardization) matters
Why we add a bias (intercept) term
What weights represent mathematically
How predictions are computed using matrix multiplication
How gradient descent works step by step
A deliberate gradient descent mistake — and why it matters