Quantum Machine Learning bridges the gap between abstract developments in quantum computing and the applied research on machine learning. Paring down the complexity of the disciplines involved, it focuses on providing a synthesis that explains the most important machine learning algorithms in a quantum ...
The main focus of this book is therefore on tackling practical real-world applications of Quantum Machine Learning (QML) algorithms executable on NISQ hardware rather than adopting the more traditional quantum computing textbook approach, diligently describing standard quantum computing algorithms (Shor’s...
Learning path notebooks may be found in theMachine Learning tutorialssection of the documentation and are a great place to start. Another good place to learn the fundamentals of quantum machine learning is theQuantum Machine Learningnotebooks from the original Qiskit Textbook. The notebooks are conveni...
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network. python machine-learning deep-learning neural-network qml tensorflow optimization quantum differentiable-computing automatic-different...
Using a quantum computer to speed up one step in a textbook approach to generating random numbers proves to be a savvy strategy, and one that could make good use of quantum computers that will be available in the near future. Mohan Sarovar Article | 12 July 2023 Generation of genuine en...
This textbook is a university quantum algorithms/computation course supplement based on Qiskit. This textbook is built on a jupyter notebook framework that allows for easy reading, but it also allows readers to edit and run the code right in the textbook
Quantum Machine Learning Course. Since QML is the focus of the second lab, you might find this self-paced course helpful. It’s similar to the original Qiskit Textbook but includes some useful bonus features, like interactive quizzes.
just as it is for classical machine learning. Moreover, the training data size required for QML generalization has yet to be fully studied. Naïvely, one could expect that an exponential number of training points are needed when training a function acting on an exponentially large Hilbert space...
This manuscript is a textbook for a graduate course in quantum mechanics.I have taught this course 15-20 times and gradually developed these notes. Orginally,I used as a text Quantum Mechanics by A.S.Davydov.When that fine book went out of print,I wrote these notes following a similar syll...
Qiskit Textbook Qiskit: Qiskit is an open-source quantum computing framework that allows users to create, manipulate, and execute quantum programs. It is built on top of popular open-source libraries such as NumPy and Scipy, making it easy for users to get started with quantum computing. With...