quantum-machine-learning
OfficialMaster variational quantum ML workflows.
Authorunitarylab
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Enables learners and researchers to understand and implement variational quantum machine learning algorithms across a cohesive, multi-algorithm framework.
Core Features & Use Cases
- Comprehensive algorithm coverage: QAOA, VQE, QNN, VQC, and QCBM with practical tutorials and examples.
- End-to-end learning workflows: Demonstrations of circuit design, optimization, and evaluation across multiple backends.
- Educational and research-friendly: Clear architecture, modular SKILL.md files, and runnable scripts to reproduce experiments.
Quick Start
Run the start-up scripts under each subskill folder to begin experimenting with the algorithms.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: quantum-machine-learning Download link: https://github.com/unitarylab/quantum-skills/archive/main.zip#quantum-machine-learning Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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