The input quantum kernel will not be altered, and an optimized quantum kernel will be returned.

Inputs are expected in a shape of (N, *). Where N is a number of samples. Gradient is computed for each sample individually.

This is the Qiskit s machine learning module. There is an initial set of function here that will be built out over time. At present it has sample sets that can be used with classifiers and circuits used in machine learning applications. Class for errors returned by Qiskit's machine learning module. A neural network is a parametrized network which may be defined as a artificial neural network - classical neural network - or as parametrized quantum circuits - quantum neural network.

This is the Qiskit s machine learning module. There is an initial set of function here that will be built out over time. At present it has sample sets that can be used with classifiers and circuits used in machine learning applications. Class for errors returned by Qiskit's machine learning module.