The following are modifications or improvements to original notebooks prior to August 31, 2023. <br>

All PennyLane Python Quantum Machine Learning Demos 8/31/23 [Seminar](https://www.chemicalqdevice.com/all-pennylane-python-quantum-machine-learning-demos-seminar). <br>

Please refer to the authors' models for the published primary work.<br>

[PL13 Equivariant Graph Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_equivariant_graph_embedding),<br>

[PL14 Time Series Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_univariate_qvr), <br>

[PL15 Geometric QML Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_geometric_qml),<br>

[PL16 Generalization in QML Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_learning_few_data), <br>

[PL17 Function Fitting Original PennyLane Model](https://pennylane.ai/qml/demos/function_fitting_qsp),<br>

[PL18 Many Body Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_ml_classical_shadows),<br>

[PL19 Learn from Experiments, Classification Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_learning_from_experiments),<br>

[PL20 Tensor Network Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_tn_circuits),<br>

[PL21 Approximate Kernel Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_classical_kernels),<br> 

[PL22 Quantum GANs Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_quantum_gans),<br>

[PL23 Unitary Designs Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_unitary_designs),<br>

[PL24 Quantum Kernels, Classification Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_kernels_module),<br>

[PL25 Haar Measure Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_haar_measure),<br>

[PL26 Learn QNNs, Speed Original PennyLane Model](https://pennylane.ai/qml/demos/learning2learn),<br>

[PL27 Kernel Scikit-Learn Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_kernel_based_training),<br>

[PL28 Keras Layers Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_qnn_module_tf),<br>

[PL29 Torch Layers Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_qnn_module_torch),<br>

[PL30 Fourier Series Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_expressivity_fourier_series),<br>

[PL31 Quantum Graph RNN Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_qgrnn),<br>

[PL32 Quanvolutional NN Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_quanvolution),<br>

[PL33 Ensemble Classification Original PennyLane Model](https://pennylane.ai/qml/demos/ensemble_multi_qpu),<br>

[PL34 Quantum Transfer Learning Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_quantum_transfer_learning),<br>

[PL35 Photonic Quantum NN Original PennyLane Model](https://pennylane.ai/qml/demos/quantum_neural_net),<br>

[PL36 GANs Cirq TensorFlow Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_QGAN),<br>

[PL37 Data-Reuploading Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_data_reuploading_classifier),<br>

[PL38 Variational Classifier Original PennyLane Model](https://pennylane.ai/qml/demos/tutorial_variational_classifier).