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sonamghosh/quantum-machine-learning: This repo is to contain material from the U ...

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

sonamghosh/quantum-machine-learning

开源软件地址(OpenSource Url):

https://github.com/sonamghosh/quantum-machine-learning

开源编程语言(OpenSource Language):

Jupyter Notebook 80.4%

开源软件介绍(OpenSource Introduction):

Quantum Machine Learning course by Prof. Peter Wittek from the University of Toronto on edx

This repository will include material covered by the online course including tutorial scripts for topics (written as .py files) and jupyter notebooks corresponding to the assignments.

In the future, there will be hopefully be typed up notes for each topic on LaTeX

Update 03/24/19

On further thought and to prevent anyone copying solutions, I will be pushing solutions to assignments only after the designated assignment due date. I still intend on keeping this repo public for educational purposes as I believe maybe for the individuals who couldn't solve a particular problem, the solution might guide them and since this course isn't giving college credit of any sort, there is no reason to believe that there will be any harm done with having these solutions up.

I do intend on the future (hopefully) to type up notes on the material (will more or less look like Peter's whiteboard material + maybe additional content and explanations).

If there is any other issue, please open up an issue on Github and not directly call me out anonymously on the edx forums unless it is an official staff member.

Thank you

Update 04/22/2019

The course has been completed. All assignment solutions are on the github. If there are any issues, open up a issue. If you think there are better or more elegant solutions, do a pull request or open an issue. Do keep in mind, all assignments are done on Rigetti's Forest framework and not IBM Q. If this course becomes available again in the future for UofT, I will temporarily make the repo privateto avoid any cheating (assuming assignments are kept the same).

Acknowledgements

Prof. Peter Wittek from the University of Toronto,

Patrick Huembeli from the Institute of Photonic Sciences.

Arthur Pesah from the KTH Royal Institute of Technology in Stockholm

Any additional staff members part of the UTQML101x course team

Contributing

Pull requests are welcome. For major changes, please open an issue first to dicuss what you would like to change.

-Sonam Ghosh




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