Recently, quantum machine learning algorithms have become popular due to a drastic increase in the power of quantum computation. Analysis of images with 10^54 pixels, easy encoding of Fourier series-like data, generation of novel chemical molecules - and all that with a couple of Python code lines! It's only left to choose a framework for trying out next-level deep learning models ... but which one? The "grandfather" of Python quantum computing packages, PennyLane, with tons of user-friendly tutorials - or maybe a Qiskit, which runs naturally on IBM quantum computers, and moreover in February 2024 got a first major release?

The answer is not that obvious, and together, we'll look at the pros and cons of both via training quantum circuits, assessing compatibility with popular Python machine learning packages - and all that on examples of real-world problems from financial and natural sciences.