Title M2S2 - Linear Model Regression, L1, L2.pdf ✅

Machine Learning Algorithms CS0077
M2S1 Linear Regression, L1, L2 Supplementary Material
• Linear models generate a formula to create a best-fit line to predict unknown values. • Linear models make a prediction using a linear function of the input features. • They are called linear because they assume there is a linear relationship between the outcome variable and each of its predictors. Linear Models in ML
Linear Models in ML Application of Linear Models Several real-life scenarios follow linear relations between dependent and independent variables. Some of the examples are: • The relationship between the boiling point of water and change in altitude. • The relationship between spending on advertising and the revenue of an organization. • The relationship between the amount of fertilizer used and crop yields. • Performance of athletes and their training regimen.