n this video, we’ll explore the basics of linear regression, one of the most common techniques used in data science and statistics. Linear regression is a method used to model the relationship between a dependent variable (what you want to predict) and an independent variable (the input you use to make predictions). The goal is to find the best-fitting straight line through the data points. br br We’ll discuss how the line is determined using the formula: br br y=mx+b br Where: br br br y is the dependent variable (the value you’re predicting), br br x is the independent variable (the input data), br br m is the slope of the line (how much br br y changes with br br b is the y-intercept (the value of br br By fitting this line to your data, you can make predictions and understand trends. We’ll break down the concept with examples and explain how it’s applied in real-world scenarios like predicting prices, trends, and more.