As mentioned earlier, regression algorithms play a crucial role in predicting continuous numeric values. These algorithms are specifically designed to make predictions for various scenarios, such as forecasting house prices, estimating flight ticket prices, predicting stock prices, projecting product sales, and more. By leveraging regression algorithms, data scientists can generate valuable insights and predictions for a wide range of real-world applications.
Linear Regression
Linear regression serves as a predictive modeling technique employed to estimate the value of one variable based on another variable. The variable to be predicted is referred to as the dependent variable, while the variable used for prediction is known as the independent variable. To delve deeper into the concept of Linear Regression and gain a comprehensive understanding, I recommend watching the video provided below.
In addition, the video will also highlight the distinction between Linear Regression and Logistic Regression, which will be discussed in subsequent sessions. Understanding this differentiation will be valuable as you progress in your learning journey.