Specific topics (Machine learning with quantum computers)
- An Introduction to Quantum Machine Learning and a Review of the Background
- Working through a K-Nearest Neighbor toy example using interference circuits
- Machine Learning methods (Linear models, Neural Networks, Graphical Models, Kernel Methods)
- ,Important quantum algorithms (State overlap measuring, Grover search, Quantum Phase Estimation, Matrix multiplication and inversion, Variational quantum algorithms)
- Data Encoding methods
- Variational Circuits as machine learning models
- Kernel-based methods
- Probabilistic Models
- Future perspective of Quantum Machine Learning