This page lists down the practice tests / interview questions and answers for Linear (Univariate / Simple Linear) / Multiple (Multilinear / Multivariate) regression in machine learning. Those wanting to test their machine learning knowledge in relation with linear/multi-linear regression would find the test useful enough. The goal for these practice tests is to help you check your knowledge in numeric regression machine learning models from time-to-time. More importantly, when you are preparing for interviews, these practice tests are intended to be handy enough. Those going for freshers / intern interviews in the area of machine learning would also find these practice tests / interview questions to be very helpful.
This test primarily focus on following two concepts related with evaluation of linear regression models:
- Coefficient of determination (R-squared)
- Pearson correlation coefficient
Note that the above two concepts are used to understand some of the following:
- Impact of one or more parameters on the dependent variable in positive or negative manner
- Overall impact/performance of regression model based on addition of one or more independent variables
Other tests in the series includes some of the following:
[wp_quiz id=”5774″]
In case you have not scored good enough, it may be good idea to go through basic machine learning concepts in relation with linear / multi-linear regression. Following is the list of some good courses / pages:
Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.
- Agentic Reasoning Design Patterns in AI: Examples - October 18, 2024
- LLMs for Adaptive Learning & Personalized Education - October 8, 2024
- Sparse Mixture of Experts (MoE) Models: Examples - October 6, 2024
I found it very helpful. However the differences are not too understandable for me