Tutorials to introduce core QML concepts, including quantum nodes, optimization, and devices, via easy-to-follow examples.
Read the documentation, see the source code, make a bug report, and contribute directly to PennyLane.
The TensorFlow of quantum computing: built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily!
Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy, PyTorch, or TensorFlow, allowing hybrid CPU-GPU-QPU computations.