The following tutorial introduce the core PennyLane concepts, including QNodes, plugins, and devices, via simple and easy-to-follow implementations.
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:tooltip: Use quantum machine learning to rotate a qubit.
:figure: beginner/qubit_rotation/bloch.png
:description: :doc:`tutorial/tutorial_qubit_rotation`
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:tooltip: Use quantum machine learning to tune a beamsplitter.
:figure: beginner/gaussian_transformation/gauss-circuit.png
:description: :doc:`tutorial/tutorial_gaussian_transformation`
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:tooltip: Use quantum machine learning in a multi-device quantum algorithm.
:figure: beginner/plugins_hybrid/photon_redirection.png
:description: :doc:`tutorial/tutorial_plugins_hybrid`
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:tooltip: Multiple expectation values, Jacobians, and keyword arguments.
:description: :doc:`tutorial/tutorial_advanced_usage`
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:tooltip: Extend PyTorch with real quantum computing power.
:figure: beginner/pytorch_noise/bloch.gif
:description: :doc:`tutorial/pytorch_noise`
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:tooltip: Explore quantum chemistry in PennyLane.
:figure: beginner/quantum_chemistry/water_structure.png
:description: :doc:`tutorial/tutorial_quantum_chemistry`
.. toctree::
:maxdepth: 2
:caption: Beginner tutorial
:hidden:
tutorial/tutorial_qubit_rotation
tutorial/tutorial_gaussian_transformation
tutorial/tutorial_plugins_hybrid
tutorial/tutorial_advanced_usage
tutorial/pytorch_noise
tutorial/tutorial_quantum_chemistry