Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the concept of broadcasting in numpy, which describes how numpy adapts two scalar objects or ndarrays of different geometries to perform operations between them. It also explains operations, comparisons, and mathematical operations like addition, subtraction, multiplication, and division between ndarrays. Additionally, it introduces numpy constants such as pi, e, Euler's constant, infinity, negative infinity, zero, and NaN. The lecture demonstrates examples of broadcasting that work and those that do not work, along with practical applications like finding the mean, variance, and standard deviation along an axis.