Simple and Basic Evaluation Metrics for Regression

Explore essential evaluation metrics for regression problems in this 31-minute video tutorial. Learn about mean absolute error, mean squared error, root mean squared error, root mean squared logarithmic error, and R2 score. Follow along as the instructor implements these metrics using the mlframework, available on GitHub. Gain practical insights into assessing regression model performance and understand how to interpret each metric. By the end of the tutorial, acquire the knowledge to effectively evaluate and compare regression models using these fundamental metrics.

Introduction
Absolute Error
Mean Square Error
Regression Matrix
Metrics
Python Implementation