co9olguy
commented
3 years ago Thanks for the submission! We hope you have enjoyed participating in QHack :smiley:
We will be assessing the entries and contacting the winners separately. Winners will be publicly announced sometime in the next month.
We will also be freezing the GitHub repo as we sort through the submitted projects, so you will not be able to update this submission.
Team Name:
Cabriella
Project Description:
We are making a custom made python library which integrates PennyLane with python.
The aim of this library is to make quantum machine learning easier to do by removing the need to encode hardware such as circuit, device, QNode etc. Our Wrapper automatically customizes the circuit according to the input, hence removing the need to understand the physics of gates, qubit interaction etc. We do this from the motivation that why classical machine learning get to not think about hardware, whereas quantum machine learners do.
The aim of this wrapper is to make qml more accessible to the classical ml users, paving the way for people to easily use qml in their projects.
Presentation:
A hyperlink to an explanatory presentation of your team’s hackathon project in a non-technical form (e.g., video, blog post, jupyter notebook, website, slideshow, etc.).
Source code:
A hyperlink to the final source code for your team's hackathon project (e.g., a GitHub repo). https://github.com/SaadNaeem96/QHack-2021-by-XanaduAI/tree/main/Hackathon