Reference

Generated from the docstrings in the source, so it cannot drift from the code.

Section	What lives there
Core	The circuit IR, gates, observables, execution, backends
Gradients	Six estimators behind one grad()
Encoding	Angle, amplitude, basis and Pauli feature maps
Ansatz	The block vocabulary, the template zoo, re-uploading
Kernels	Overlap estimators, Gram matrices, QSVC/QSVR
PyTorch	QuantumLayer, VQC, structured architectures
Algorithms	VQE, QAOA, ADAPT, chemistry, autoencoders, clustering, RL
Analysis	Metrics, Fourier spectra, quantum information, optimisers
Evaluation	Scores, class imbalance, classical baselines, budget, provenance

If you are looking for the shape of the library rather than a particular function, the tutorials are the faster route.