Linear Predictive Models

#artificialintelligence 

Welcome readers to Part 2 of the Linear predictive model series. If you haven't read Part 1 of this series, you can read that here: As a quick recap, in part 1 we obtained our data by web scraping AutoScout24 and obtained the dataset of car sales in Germany. Next, we cleaned and prepared the data for a preliminary Exploratory data analysis. Then we began with our modeling and used several Regression models like Linear regression with and without regularization, Linear regression with Regu, Pipeline, Cross Val Predict, and lastly with Polynomial regularization. Regression analysis can be described as a way of predicting the future of a dependable (target) variable use single or multiple independent variables(also known as predictors).

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