PyTorch Tutorial for Beginners: Build a Multiple Regression Model from Scratch

A multiple linear regression model is built to predict abalone age using physical measurements from a well-known dataset. The process begins with data preparation and extensive exploratory data analysis, which uncovers issues like non-normal distributions, multicollinearity, and heteroscedasticity. An initial baseline model is created using Scikit-Learn, highlighting the dataset's inherent challenges and the model's struggles with accurate predictions. To improve performance, techniques such as outlier removal using Local Outlier Factor and feature engineering by adding second-order variables are applied, resulting in a modest improvement in RMSE and adjusted R-squared.