Practical Data Science using Python - Linear Regression Model Building

The video tutorial explains the process of splitting a dataset into training and test sets for building a machine learning model, specifically linear regression. It emphasizes the importance of using separate data for training and testing to ensure the model's accuracy. The tutorial covers data scaling using MinMaxScaler and preparing predictor and target variables. It details the model building process using ordinary least squares and evaluates model performance using R-squared and adjusted R-squared values.

What new insight or understanding did you gain from this video?

Evaluate responses using AI:

OFF