qcml

A benchmarking library for quantum and classical machine learning, with specialized support for evaluating kernel methods.

https://github.com/albertnieto/qcml

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 1 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Academic email domains
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  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (8.2%) to scientific vocabulary

Keywords

benchmarking kernel-methods machine-learning pennylane qiskit quantum-computing quantum-machine-learning
Last synced: 4 months ago · JSON representation ·

Repository

A benchmarking library for quantum and classical machine learning, with specialized support for evaluating kernel methods.

Basic Info
  • Host: GitHub
  • Owner: albertnieto
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 3.27 MB
Statistics
  • Stars: 7
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Topics
benchmarking kernel-methods machine-learning pennylane qiskit quantum-computing quantum-machine-learning
Created about 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing License Citation

README.md

Quantum Computing Utilities for Python

DOI

This library is dedicated to quantum computing, featuring gate implementations, algorithms, and utilities. This repository serves as a recollection of assignments and utilities developed for the Master's program in Quantum Computing at UNIR. It includes educational assignment documents and a set of Jupyter notebooks for learning purposes.

Overview

This library is designed to provide developers with a comprehensive set of tools and functionalities for quantum computing. It includes modules for gate implementations, handling various quantum notations, managing quantum states, utilities for quantum operations, as well as educational assignment documents and Jupyter notebooks.

Developers interested in quantum computing can use it to explore quantum algorithms, experiment with gate implementations, manipulate quantum states, and leverage utilities to enhance their understanding and development in the quantum computing domain.

Contributions

Contributions are welcome and encouraged! Whether you want to add new functionalities, improve existing modules, enhance documentation, fix issues, or contribute to educational Jupyter notebooks, feel free to contribute by submitting a pull request.

License

This repository is licensed under the MIT License.

Owner

  • Name: Albert
  • Login: albertnieto
  • Kind: user

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Nieto Morales"
  given-names: "Albert"
  orcid: "https://orcid.org/0009-0007-5060-6157"
title: "qcml"
version: v.0.1.0-alpha
doi: 10.5281/zenodo.13632282
date-released: 2024-09-02
url: "https://github.com/albertnieto/qcml"

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Packages

  • Total packages: 1
  • Total downloads:
    • pypi 44 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 8
  • Total maintainers: 1
pypi.org: qcml

A benchmarking library for quantum and classical machine learning, with specialized support for evaluating kernel methods.

  • Versions: 8
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 44 Last month
Rankings
Dependent packages count: 10.3%
Average: 34.3%
Dependent repos count: 58.2%
Maintainers (1)
Last synced: 5 months ago

Dependencies

requirements.txt pypi