Advanced PyTorch and TensorFlow Deep Learning with QML and QiML Layers

Explore advanced techniques for integrating quantum algorithms into machine learning frameworks in this comprehensive 1-hour presentation. Learn practical methods to incorporate quantum 'layers' into PyTorch and Keras platforms through benchmarking quantum simulators, strategically inserting layers into neural networks, and discovering other potential applications. Access example notebooks using Qiskit and PennyLane to gain hands-on experience with quantum machine learning concepts. Dive into the intersection of quantum computing and deep learning to unlock innovative approaches for solving complex problems in both fields.