The main advantage of evolutionary optimization is that, unlike many machine learning training algorithms, it does not require a Calculus gradient. The main disadvantage of evolutionary optimization ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Although the classical machine learning community focuses on gradient-based parameter optimization, finding near-exact gradients for variational quantum circuits (VQCs) with the parameter-shift rule ...

Using a range of real datasets and basic Python libraries for data manipulation, vector/matrix algebra, and automatic differentiation students will code up - from scratch - fundamental optimization ...