# Useful Resource

## Quantum Machine Learning

### Video
* [Qfort-An Introduction to Quantum Machine Learning](https://www.youtube.com/watch?v=Js4O9k3m0ZY)
* [Quantum Neural Network - Kerstin Beer](https://www.youtube.com/watch?v=HfmmZregVDU)
### Paper
* [Supervised learning with quantum-enhanced feature spaces](https://www.nature.com/articles/s41586-019-0980-2)
* [Quantum Support Vector Machines for Continuum Suppression in B Meson Decays](https://link.springer.com/article/10.1007/s41781-021-00075-x)
* [_Kernel-based quantum regressor models learning non-Markovianity]
* [Experimental kernel-based quantum machine learning in finite feature space](https://www.nature.com/articles/s41598-020-68911-5)
* [Estimating the degree of non-Markovianity using machine learning](https://journals.aps.org/pra/abstract/10.1103/PhysRevA.103.022425)
* [Investigation of Quantum Support Vector Machine for Classification in NISQ era](https://arxiv.org/pdf/2112.06912.pdf)
### Website
## Quantum Annealing
### Video
* [Qfort-Solving NP-hard Problems with Quantum Annealing](https://www.youtube.com/watch?v=7CpdhL7GcD4)

### Paper

### Website
## Quantum Computing

### Video
### Paper
* [QAOA](https://arxiv.org/pdf/1411.4028.pdf)
### Website
* [Algorithm Zoo](https://quantumalgorithmzoo.org/)

## Quanutum Open System
### Paper
* [Measure for the Degree of Non-Markovian Behavior of Quantum Processes in Open Systems](https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.103.210401)