Making Linear Predictions in PyTorch
Linear regression is a statistical technique for estimating the relationship between two variables. A simple example of linear regression is to predict the height of someone based on the square root of the person’s weight (that’s what BMI is based on). To do this, we need to find the slope and intercept of the line. The slope is how much one variable changes with the change in other variable by one unit. The intercept is where our line crosses with the $y$-axis.
Let’s use the simple linear equation $y=wx+b$ as an example. The output variable is $y$, while the input variable is $x$. The slope and $y$-intercept of the equation are represented by the letters $w$ and $b$, hence