General parameter-shift rules for quantum gradients
-
Updated
Jun 18, 2024 - Mathematica
General parameter-shift rules for quantum gradients
Hands-on quantum computing for machine learning, built from scratch in NumPy then bridged to PennyLane. 6-week course: qubits & gates, entanglement & CHSH, quantum algorithms (Deutsch–Jozsa, Grover, QFT), variational circuits & VQE, quantum ML classifiers, and quantum kernels.
Add a description, image, and links to the parameter-shift topic page so that developers can more easily learn about it.
To associate your repository with the parameter-shift topic, visit your repo's landing page and select "manage topics."