In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model.

I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

In the worked example we already considered above, if we run the multiple linear regression, we would generate a 95% confidence interval (CI) around the regression coefficient for age, which is a ...

Figure 1: The results of multiple linear regression depend on the correlation of the predictors, as measured here by the Pearson correlation coefficient r (ref. 2). ( a ) Simulated values of ...