Welcome to the module on ‘Advanced Regression’. In the previous modules, you learnt about the principles of model selection, model simplicity and complexity, overfitting, regularisation, etc., for linear data.
In this module
You will learn how to extend the linear regression framework to problems that are not strictly ‘linear’ and understand the differences between linear and nonlinear regression problems. We will also deal with the regularisation techniques that are used to reduce overfitting in linear regression. In the forthcoming video, Anjali will give you an overview of this module.
Learning Objectives
- Build linear regression models in the presence of non-linearity in data.
- Build linear regression models in Python to handle the non-linearity present in data.
- Understand and use Ridge and Lasso regularisation to handle overfitting due to the increase in model complexity.
- Build a regularised linear regression model in Python using both the Ridge and Lasso methods.
In this session
- We will recall the basics covered in the Linear Regression module.
- Then we will try to find the model coefficients in linear regression with the help of normal equations and matrix representations.
- At the end, we will also discuss the assumptions for linear regression and ways to assess them using residual plots.
Files used in this session
Guidelines for in-module questions
The in-video and in-content questions given at the end of each segment are not graded. Note that graded questions are provided in a separate segment titled ‘Graded Questions’ at the end of this session. These graded questions will adhere to the guidelines given below.
First Attempt Marks | Second Attempt Marks | |
| Questions With 2 Attempts | 10 | 5 |
| Questions With 1 Attempt | 10 | 0 |
People you will hear from in this session
Faculty/ Adjunct Faculty
Sr. Subject Matter Expert, upGrad
Anjali has over 18 years of experience and has worked as a software engineer, data scientist and a project lead in companies like Infosys and Evalueserve across geographies. She is currently working as a senior subject matter expert at upGrad.