We often talk about the gradient of a scalar function as being the direction of steepest ascent. Rather than taking that for granted, let's convince ourselves that it is true. This is part of a series of videos for COS 302: Mathematics for Numerical Computation and Machine Learning, replacing lectures after the course went remote due to the COVID-19 pandemic.
Laboratory for Intelligent Probabilistic Systems
Princeton University Department of Computer Science