The Qiskit Global Summer School 2021 was a two-week intensive summer school designed to empower the next generation of quantum researchers and developers with the skills and know-how to explore quantum applications on their own. This second-annual course, made up of twenty lectures, five applied lab exercises, hands-on mentorship, and live Q&A sessions, focused on developing hands-on experience and understanding of quantum machine learning.
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[Quantum Neural Networks explained in 3Blue1Brown style animation --- Youtube Video List]
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[Quantum Machine Learning MOOC --- Youtube Video List] created by Peter Wittek from the University of Toronto in Spring 2019.
- [arXiv:2502.01146] Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers, Yuxuan Du, Xinbiao Wang, Naixu Guo, Zhan Yu, Yang Qian, Kaining Zhang, Min-Hsiu Hsieh, Patrick Rebentrost, Dacheng Tao [Paper] [Code]
- 本源量子
- [TorchQuantum Examples]
- [MIT-HAN-LAB-GitHub] A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.
- [DeepQuantum] [GitHub]