Regression and Prediction with stats models python (numeric response and feature variables) скачать в хорошем качестве

Regression and Prediction with stats models python (numeric response and feature variables)

In this video, I would like to explore performing regression and prediction using python stats models. Here I will be focusing on numeric variables as both my response and feature variables. The content is solely for educational purposes and is based on my personal experience. Links: Dataset - https://www.kaggle.com/datasets/zynic... Code - https://github.com/maddyhyc/Regressio... See other links to sites that I used to hone my skills below. I may receive commission from them. BE SURE TO CHECK THEM OUT! Datacamp signup and learn for free - https://datacamp.pxf.io/c/3053810/161... Datacamp student - https://datacamp.pxf.io/c/3053810/161... Datacamp business - https://datacamp.pxf.io/c/3053810/154... Canva - https://partner.canva.com/FwDbyMaddy Timestamps: 00:00 Introduction 00:15 Using chatgpt 01:31 Import packages and read in first wine dataset 02:31 Inspect data - info, describe, scatterplot 04:12 Drop missing values 04:59 Fit linear regression model using ols 05:53 Read in second wine dataset and manipulate data 07:50 Predict price using model using points in second wine dataset 08:36 Analyze the predicted price and plot results 09:36 Evaluate model performance r-squared 10:32 Evaluate model performance residual standard error 11:17 Alternate method to calculating use 11:59 Final thoughts