Linear regression & multiple linear regression скачать в хорошем качестве

Linear regression & multiple linear regression

The main idea of the video is to introduce the concept of linear regression, a statistical method used to model the relationship between a dependent variable & 1 or more independent variables. The video focuses on 2 types of linear regression: Simple Linear Regression (SLR): This type involves 1 independent variable & is used to find a linear relationship between the predictor variable (X) & the target variable (Y). The video explains how to fit a simple linear regression model in Python using the scikit-learn library & how to interpret the model's parameters (intercept & slope). Multiple Linear Regression (MLR): This type involves multiple independent variables & is used to model the relationship between the target variable & a combination of predictors. The video provides a brief overview of MLR, including how to fit & predict using multiple predictors in Python. The video also discusses the concept of noise in the data & how it affects the accuracy of the model's predictions. It emphasizes that linear regression models are not always perfect & that there will always be some degree of error in the predictions.