Understanding Multiple Linear Regression

With video explanation | Data Series | Episode 4.4

We have taken a look at Simple Linear Regression in Episode 4.1 where we had one variable x to predict y, but what if now we have multiple variables, not just x, but 𝑥₁,𝑥₂ and 𝑥₃ … to predict y — how would we approach this problem? I hope to explain in this article.

Simple Linear Regression Recap

From Episode 4.1 we had our data of temperature and humidity:

We plotted our Data, found and found a linear relationship — making linear regression suitable:

We then calculated our regression line:

using gradient descent to find our parameters θ₀ and θ₁.

We then used the regression line calculated to make predictions for Humidity given any Temperature value.

What is Multiple Linear Regression?