Non-linear transformations are mathematical operations that change data in a way that is not proportional or straight-line. Unlike linear transformations, which maintain a constant ratio, non-linear transformations can curve or bend the data, allowing for more complex relationships to be modeled. This is often used in fields like statistics and machine learning to better fit data to a desired outcome. Common examples of non-linear transformations include exponential, logarithmic, and polynomial functions. These transformations can help in analyzing data that has varying rates of change, making it easier to identify patterns or trends that might not be visible with linear methods.