Regression Models
Regression models are statistical techniques used to model and analyze the relationship between a dependent variable and one or more independent variables. They are fundamental in machine learning and data science for predicting continuous outcomes, identifying trends, and understanding causal effects. Common types include linear regression, logistic regression, and polynomial regression.
Developers should learn regression models when building predictive analytics systems, such as forecasting sales, estimating housing prices, or analyzing user behavior in applications. They are essential for data-driven decision-making in fields like finance, healthcare, and marketing, providing interpretable insights and enabling accurate predictions based on historical data.