Floating Point Numbers: Representation and Errors

This lecture covers the representation of floating point numbers, including fixed-point and floating-point representations. It discusses the importance of choosing the right representation for numerical algorithms, highlighting the impact of errors in floating-point arithmetic. The instructor explains the concept of relative error and its implications in numerical computations, emphasizing the need for understanding the limitations of floating-point precision. Various examples are provided to illustrate the challenges of representing real numbers in a discrete computational environment.